Multiple Criteria Decision Making: From Early History To The 21st Century 9789814335591, 9789814335584

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Multiple Criteria Decision Making From Early History to the 21st Century

Murat Koksalan

V

Jyrki Wallenius Stanley Zionts

A

World Scientific

Multiple Criteria Decision Making From Early History to the 21st Century

8042.9789814335584-tp.indd 1

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Multiple Criteria Decision Making From Early History to the 21st Century

Murat Köksalan Middle East Technical University, Turkey

Jyrki Wallenius Aalto University, Finland

Stanley Zionts SUNY Buffalo, USA

World Scientific NEW JERSEY

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8042.9789814335584-tp.indd 2

LONDON

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SINGAPORE

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BEIJING

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SHANGHAI

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HONG KONG

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TA I P E I

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CHENNAI

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Published by World Scientific Publishing Co. Pte. Ltd. 5 Toh Tuck Link, Singapore 596224 USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE

British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library.

MULTIPLE CRITERIA DECISION MAKING From Early History to the 21st Century Copyright © 2011 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means, electronic or mechanical, including photocopying, recording or any information storage and retrieval system now known or to be invented, without written permission from the Publisher.

For photocopying of material in this volume, please pay a copying fee through the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. In this case permission to photocopy is not required from the publisher.

ISBN-13 978-981-4335-58-4 ISBN-10 981-4335-58-4

Typeset by Stallion Press Email: [email protected]

Printed in Singapore.

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Contents

Preface

vii

Chapter 1

The Early History of MCDM

1

Chapter 2

MCDM Developments in the 1970s

17

Chapter 3

MCDM Developments in the 1980s

31

Chapter 4

MCDM Developments in the 1990s and Beyond

43

Chapter 5

MCDM Conferences

63

Chapter 6

MCDM Society Traditions

89

Chapter 7

Awards and Presidents

93

Chapter 8

Biographies of Leading MCDM Scholars

95

Chapter 9

Conclusion

157

References

161

Subject Index

185

Name Index

191

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What led to the writing of this book? The field of Multiple Criteria Decision Making (MCDM) can be said to be both old and new, depending on one’s frame of reference. It is old because people have always had to trade off objectives in making decisions. Possibly the first recorded discussion of trade-offs in making decisions and consideration of multiple objectives is the American statesman Benjamin Franklin’s way of deciding his position on important decisions. Franklin lived during the 1700s. Many modern researchers have considered MCDM problems. The problem may be represented as an evaluation problem, where the decision maker chooses among a finite set of discrete alternatives; or as a design problem, where the set of decision alternatives is described with a mathematical model. Among the research, the work of Abraham Charnes and William Cooper on goal programming in the late 1950s was a major stimulus to the later explosion of MCDM work. Since then, more than 15,000 papers and numerous books have been written, all of which can be regarded as MCDM contributions from the 1960s to the present time. Hence MCDM is clearly an important subfield of Management Science or Operations Research, or as a matter of fact, an important field in its own right. The MCDM field has experienced exponential growth in terms of the number of publications as well as the number of citations. The roots of the field are relatively old, extending to research of classical economists and mathematicians. Recent foundations of MCDM were developed in the 1950s and 1960s. The 1970s was an important decade in which many seminal contributions were produced, with the field maturing during the 1980s. MCDM experienced accelerated development during the early 90s and seems to have continued its vii

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exponential growth. As an outcome of the growth many subfields have emerged. A recent subfield is Evolutionary Multiobjective Optimization (EMO), in which there have been many active researchers. Interestingly, MCDM has penetrated and continues to penetrate many engineering fields, as well as medicine. The initials MCDM, of course, stand for Multiple Criteria Decision Making. A paper by Stan Zionts, entitled “MCDM — If not a Roman Numeral, then What?” published in 1979, helped make MCDM an accepted abbreviation for the field. The book by Saul Gass and Arjang Assad, An Annotated Timeline of Operations Research: An Informal History published in 2005, provided an impetus for writing this book. The Gass–Assad volume explored the timeline of Operations Research, as well as many of its developments. It also includes biographies of many contributors to the field. Though some MCDM contributors and contributions are included in their book, many are not or are just very briefly mentioned. Therefore we thought of producing a book devoted only to MCDM, its contributions and contributors. We consider MCDM to consist of many subfields, such as Decision Analysis, Goal Programming, work of the “French School,” which includes outranking relations, Multiple Objective Mathematical Programming, Fuzzy Set Theory, the Analytic Hierarchy Process (AHP), and Evolutionary Multiobjective Optimization (EMO). We have tried to include all important subfields, contributions, and contributors in compiling this volume. Any omissions are ours, and we apologize in advance for them. The criteria we used to select contributions and contributors for the volume came from various sources. We used citation statistics from the ISI Web of Science and Google Scholar, a powerful search engine provided under the Google umbrella. We included contributions and contributors we felt were important to the field, well known scholars and their contributions. We were sure to include recipients of our society’s (the International Society on Multiple Criteria Decision Making) awards and their main contributions (there have been 34 awards to date — given at meetings of the society). We decided to organize the book chronologically. We begin with the early history of MCDM, which covers the roots of MCDM through the

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1960s. Then we proceed decade by decade, with one chapter each covering the 1970s, the 1980s, as well as the 1990s and beyond. The impact of recent developments have not yet been fully observed. Therefore, we included the developments in the 2000s together with the 1990s and tried to concentrate on trends observed during that decade. We also mention highlights of the twenty conferences that our society has had. The most recent MCDM conference took place in Chengdu, Sichuan Province, China in June, 2009; the next one is scheduled for Jyväskylä, Finland in June 2011. Each meeting has been unique: we have had conferences in more than a dozen countries around the world. Some have been lavish; others have been less so. Yet each has made its mark in its own way, both in terms of research presented and in terms of the culture of the host area and the hosts. We did not however, adhere strictly to the chronological order. If a topic is covered only in a certain section, we mention the developments from other decades in that section as well. In some other cases, we decided to discuss topics across different decades to maintain continuity. We have included brief biographies with pictures of major contributors, which allow for interesting stories and lives to emerge. We obtained help for the biographies and pictures from contributors to the field where possible but used other sources as well. We have also, when possible, included personal aspects of the contributors’ lives, emphasizing the human side of the researchers. One of our inspirations for this book project was Murat Köksalan’s presentations in his classes, which summarize major developments in the field together with the pictures of prominent MCDM scholars. We tried to produce a proper mixture of pictures and history. Why us? Why did we write this book? What are our qualifications for writing such a book? We are all seasoned MCDM scholars, with a collective memory extending back to the 60s. Murat Köksalan, a graduate of the State University of New York (SUNY) Buffalo (under Mark Karwan and Stan Zionts) served many years as a member of the Executive Committee of the International Society on Multiple Criteria Decision Making. He was a past chairperson of the Society’s Awards Committee and the chairperson of the organizing committee for the 15th International MCDM Conference held in Ankara, Turkey. He is the

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founding president of the INFORMS Section on MCDM. His research has included problems of Multiple Criteria Decision Making, multiobjective combinatorial optimization, decision support, heuristic search and evolutionary algorithms, among others. He was awarded the Gold Medal of the International Society on Multiple Criteria Decision Making in 2006. Jyrki Wallenius is the current President of the International Society on Multiple Criteria Decision Making. His research has covered problems of Multiple Criteria Decision Making, negotiation analysis, behavioral decision making, decision support, and online auctions. Wallenius is a former editor of the European Journal of Operational Research. He received the Edgeworth–Pareto award from the International Society on Multiple Criteria Decision Making in 1994. Stanley Zionts is Distinguished Professor Emeritus at the State University of New York at Buffalo, where he served on the faculty from 1967 until 2005. He served as Professor of Management at the European Institute for Advanced Studies in Management in Brussels from 1973 to 1975, where Wallenius was his student. Zionts was the founder and first president of the Special Interest Group on MCDM, a predecessor of the International Society on Multiple Criteria Decision Making. Under his leadership the society grew into an international organization with membership of over 1,000 scholars in about 80 different countries. He was the organizer of several international MCDM conferences. His research has included various aspects of linear and integer programming, Multiple Criteria Decision Making, negotiation analysis, decision support, and finance. Zionts was awarded the Gold Medal as well as the Presidential Service Award of the International Society on Multiple Criteria Decision Making in 1992. Many of the pictures are from the authors’ private sources or the contributors themselves. In addition, we have obtained permission to reuse pictures from various sources, including Princeton University, The Archives of the Mathematisches Forschungsinstitut Oberwolfach, and Aalto University School of Economics. Some pictures are in the public domain. Many people have helped us with the compilation of information in this volume. First, we thank the contributors to the field, with whom we have been in contact. In addition, we wish to thank the many other people who have helped us with information or pictures. This

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includes Günter Fandel, Saul Gass, Pekka Korhonen, and Ralph Steuer. Saul Gass deserves a special thank you. Besides furnishing us with several pictures, he provided us with valuable advice regarding the use of pictures. We have enjoyed preparing and writing this book. It has been both fun and educational. We hope that readers, whether MCDM or related researchers, graduate students, emeritus professors, or just laypersons, enjoy reading the book as much as we have enjoyed writing it.

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Chapter 1

The Early History of MCDM

The practice of decision making is ancient. Yet, the origins of the field are somewhat obscure. We can, however, separately trace the origins of decision analysis/utility theory and the origins of multiple objective mathematical programming. The earliest known reference relating to Multiple Criteria Decision Making (although not using that name) can be traced to Benjamin Franklin (1706–1790), the American statesman, who allegedly had a simple paper system for deciding his position on an important issue. He explained his procedure in a letter to a friend, Joseph Priestly. Take a sheet of paper. On one side write the arguments in favor of a decision; on the other side the arguments against. Cross out arguments on each side of the paper that are relatively of equal importance. Franklin did in fact talk about weights, though he did not describe any actual use of weights. When all the arguments on one side have been crossed out, the side with arguments not crossed out is the side of the argument that should be supported. Franklin supposedly used this in making important decisions. Marie-Jean-Antoine-Nicolas de Caritat (better known with his title, Marquis de Condorcet, 1743–1794), a French mathematician and political scientist, was a pioneer in applying mathematics to the social sciences, in particular to elections. He wrote the famous Essay on the Application of Analysis to the Probability of Majority Decisions in 1785. This paper described Condorcet’s jury theorem, Condorcet’s paradox, and the socalled Condorcet method. Condorcet’s paradox is perhaps the most famous of his results. It states that majority preferences may become intransitive even though individual preferences are transitive. He disagreed with a contemporary scholar, another French mathematician and political scientist, Jean-Charles de Borda (1733–1794), who advocated the use of summed rankings. 1

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(Left) Benjamin Franklin (1706–1790): American statesman, author, inventor. Inspired MCDM scholars by his “Moral Algebra.” (Right) Georg Cantor (1845–1918): Mathematician whose work impacted the mathematical foundations of multiobjective optimization.

Marquis de Condorcet

Georg Cantor (1845–1918) was a German mathematician born in St. Petersburg, Russia. He is known to be the creator of set theory. He made many other fundamental contributions to mathematics. These contributions are also the foundations of the mathematical concepts used in MCDM. Since 1992, the International Society on Multiple Criteria Decision Making has been giving out Georg Cantor awards. Francis Edgeworth (1845–1926) was an influential person in the development of neoclassical economics. He was the first to apply certain

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(Left) Francis Ysidro Edgeworth (1845–1926) (Right) Vilfredo Pareto (1848–1923) developed main concepts used in MCDM.

formal mathematical concepts to decision making. He developed the foundations of utility theory, introducing the notion of an indifference curve and the famous Edgeworth box. He was appointed Professor of Economics at King’s College London in 1888, and later Professor of Political Economy at Oxford University. An Edgeworth box is a way of representing various distributions of resources. Edgeworth described the box in his famous book: Mathematical Psychics: An Essay on the Application of Mathematics to the Moral Sciences (1881). More recently, the economist Vilfredo Pareto (1848–1923), born in Paris to Italian expatriates, was the first to mathematically study the aggregation of conflicting criteria into a single composite index. He was also the first to introduce the concept of efficiency (which became known as Pareto-optimality), one of the key concepts of economics and modern MCDM theory. A Pareto-optimal allocation of resources is achieved when it is not possible to make anyone better off without making at least one other person worse off. Pareto graduated from the Polytechnic Institute of Turin in 1869. Throughout his life, Pareto actively criticized the Italian government’s economic policies, despite not studying economics seriously until he was over forty years old. In 1893, he succeeded Leon Walras as Professor of Economics at the University of Lausanne. His main

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publications are Cours d’économie politique (1896–1897) and Manual of Political Economy (1906). In 1923, Pareto was nominated to serve as a member of Mussolini’s government, but he did not wish to become a ratified member. He died shortly thereafter. In 1906, Pareto reworked Edgeworth’s original presentation into the now-familiar box representation. Given some endowment in an Edgeworth box, the contract curve is the set of Pareto-efficient allocations in a twoagent economy. Both Pareto’s and Edgeworth’s work have had profound effects on economics, negotiation science, and modern MCDM. The International Society on Multiple Criteria Decision Making has been giving out Edgeworth-Pareto awards since 1992.

Origins of Decision Analysis, Utility A discussion of the origins of decision analysis would be incomplete without mentioning the early contributions of Frank P. Ramsey (1903–1930). He presented the first set of axioms for choices between alternatives with uncertain outcomes, leading to an expected (subjective) utility model in 1926. This work was published after his death as an essay “Truth and Probability” in 1931 (Ramsey, 1931). Leonard Savage (1917–1971) followed in Ramsey’s footsteps by developing his own theory of choice which is similar to Ramsey’s, but uses different terminology. Savage summarized many of his thoughts in his 1954 book, Foundations of Statistics. In 1944, John von Neumann (1903–1957) and Oskar Morgenstern (1902–1977) introduced (their version of) expected utility theory, apparently unaware of Ramsey’s contributions, laying the foundations for a popular MCDM approach. Their monumental work Theory of Games and Economic Behavior contains a few sections on utility theory. They presented, among other things, a set of preference axioms and a method (called the method of standard gambles) for eliciting a utility function for money (or for any attribute). John Nash (born in 1928) was a fundamental contributor to noncooperative n-person games and to the solution of the so-called bargaining problem. His papers, (for example, “Equilibrium Points in n-Person Games,” and “The Bargaining Problem”) have greatly influenced modern economics. Nash received the Nobel Prize in Economics in 1994.

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Frank Plumpton Ramsey

(Left) John F. Nash Jr. Courtesy: Wikimedia Commons, http://en.wikipedia.org/wiki/List_of_Nobel_laureates_in_Economics.

(Right) John von Neumann (right) (1903–1957) and Oskar Morgenstern (left) (1902–1976), authors of the monumental volume, Theory of Games and Economic Behaviour, 1944, introduced concepts of expected utility theory. Photographer unknown. From The Shelby White and Leon Levy Archives Center, Institute for Advanced Study, Princeton, NJ, USA.

Another early contributor to utility and value theory was Gerard Debreu (1921–2004), another Nobel Laureate, who published his classic book Theory of Value: An Axiomatic Analysis of Economic Equilibrium in 1959 and an influential paper “Topological Methods in Cardinal Utility

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(Left) Gerard Debreu Courtesy: “Archives of the Mathematisches Forschungsinstitut Oberwolfach.”

(Right) Paul A. Samuelson Courtesy: Wikimedia Commons, http://en.wikipedia.org/wiki/List_of_Nobel_laureates_in_Economics.

Theory” in 1960. See also West Churchman and Russell Ackoff’s “Approximate Measure of Value” (Churchman and Ackoff, 1954). In 1938, Paul Samuelson (1915–2009) published a paper entitled “A Note on the Pure Theory of Consumer’s Behavior” in Economica, describing a concept he later called “revealed preference.” In this paper, Samuelson stated what has become known as the weak axiom of revealed preference: “… if an individual selects batch one over batch two, he does not at the same time select two over one.” The preferences of rational people are revealed (in theory) by the choices they make. Ten years later, Samuelson described how one could use the revealed preference relation to construct a set of indifference curves. The proof was for two goods only and was largely graphical. Revealed preference theory has had considerable impact on the theory of consumer behavior over the years. In later years, it has been subjected to numerous empirical tests. See Koo (1963) and Afriat (1967). The influence of revealed preference theory on modern MCDM is not obvious; perhaps because many MCDM scholars did not have a background in economics. However, it certainly did influence single-dimensional utility assessment theory and practice. Samuelson received the Nobel Prize in Economics in 1970 for his many contributions to neoclassical economics.

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Herbert A. Simon Courtesy: Wikimedia Commons, http://en.wikipedia.org/wiki/Herbert_Simon.

Ward Edwards (1927–2005) is generally regarded as the father of behavioral decision research. He published two seminal articles, one in 1954 and the other in 1961, creating behavioral decision research as a new field. In his 1954 article “The Theory of Decision Making,” Ward Edwards introduced the expected utility model to psychologists and posed the (good) question: do people actually behave as if they have a utility function? However, it was Edwards’ later publication “Behavioral Decision Theory” in 1961 that really established the field of behavioral decision making. The paper discussed issues such as how people make decisions and how one could improve decisions. In recent years, it has increasingly been recognized that we ought to have a better understanding of how humans make decisions, in order to provide decision makers better support. Another giant of decision making is Herbert A. Simon (1916–2001). Against the mainstream of economics, he claimed that decision making does not obey the postulates of the “rational man.” Simon won the Nobel Prize in Economics in 1978. In a series of articles and books starting in the 1940s, Simon wrote about decision making.1 Among other things, he 1

Allen Newell (1927–1992) and Herbert Simon are widely regarded as the fathers of artificial intelligence, a field which has also influenced modern MCDM.

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Kenneth Arrow Courtesy: Wikimedia Commons, http://en.wikipedia.org/wiki/List_of_Nobel_laureates_in_Economics.

developed a behavioral theory based on limited or bounded rationality (see “A Behavioral Model of Rational Choice,” 1955.) Simon claimed that humans are not utility maximizers, but “satisficers.” They set aspiration levels. If they are able to meet such aspiration levels, they are happy. It has been suggested that the theory has normative as well as descriptive value. Aspiration levels play a major role in modern MCDM techniques. Arrow’s impossibility theorem, or Arrow’s paradox, demonstrates that no aggregation system can convert the (ordinal) preferences of individuals into a community-wide ranking, while also meeting certain reasonable criteria with three or more discrete options to choose from. These criteria are called unrestricted domain, non-imposition, non-dictatorship, Pareto-efficiency, and independence of irrelevant alternatives. The theorem is named after economist Kenneth Arrow (born in New York City in 1921), who presented the theorem in his Ph.D. thesis and made it known in his 1951 book Social Choice and Individual Values. Arrow’s theorem has generated much research on how to “circumvent” the original difficulty, by modifying one of the assumptions. In connection with social choice theory, we would also like to mention the far-reaching contributions of Amartya Sen (1970). According to the Royal Swedish Academy of Sciences, Sen has, among other things, specified the general conditions that eliminate intransitivities of the majority rule. This discussion has

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Amartya Sen Courtesy: Wikimedia Commons, http://en.wikipedia.org/wiki/List_of_Nobel_laureates_in_Economics.

Ronald A. Howard

R. Duncan Luce Photograph taken by Carolyn Scheer Luce.

interesting connections to, for example, approval voting — a scheme devised by Steven Brams and Peter Fishburn in 1978. Arrow was a co-recipient of the 1972 Nobel Prize in Economics. R. Duncan Luce (born 1925) and Howard Raiffa (born 1924) published a book Games and Decisions: Introduction and Critical Survey in 1957, which was a predecessor of modern decision theory. Shortly thereafter, Ron Howard wrote a paper “Sequential Decision Processes” with G. E. Kimball,

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Ragnar Frisch Courtesy: Wikimedia Commons, http://en.wikipedia.org/wiki/List_of_Nobel_laureates_in_Economics.

in Notes on Operations Research in 1959. Jointly with James E. Matheson, Howard also wrote “Decision Analysis: Applied Decision Theory,” published in the Proceedings of the Fourth International Conference on Operational Research in 1966, where they supposedly used the term “decision analysis” for the first time. Howard Raiffa published two important books on decision analysis during the 60s, the first with Robert Schlaifer in 1961 (Applied Statistical Decision Theory) and the second in 1968 (Decision Analysis Introductory Lectures on Choices Under Uncertainty). The latter focuses on the popular decision tree approach. We should also mention R.D. Luce and J.W. Tukey’s original paper written in 1964 on conjoint analysis, which has become a popular “utility measurement” technique, used in particular in various marketing contexts. Unrelated to von Neumann and Morgenstern, Ragnar Frisch (1895–1973), a Norwegian Nobel Laureate in Economics, published a relatively unknown paper in 1961 titled “Numerical Determination of a Quadratic Preference Function for Use in Macroeconomic Programming” in the Italian journal Giornale Degli Economisti e Annali Di Economica. In that paper and in a sequel publication, Frisch developed an interview technique to elicit a person’s utility (value) function. Frisch very much wanted to have his utility function elicitation technique used by the Norwegian Parliament. Despite his close association with the Finance Minister, the attempt failed. The Members of Parliament simply did not wish to make their utility functions explicit!

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A very prolific contributor to utility theory was Peter Fishburn (born 1936). He made many fundamental contributions to the theory of social choice and utility during his career. Fishburn wrote two well known books in the 1960s: Decision and Value Theory in 1964 and Utility Theory for Decision Making in 1970, summarizing many of his earlier thoughts. Both books further advanced utility theory. The ELECTRE methods comprise a family of MCDM methods that originated in France during the mid-1960s. The acronym ELECTRE stands for ELimination Et Choix Traduisant la REalité (ELimination and Choice Translating REality). The method was first proposed by Bernard Roy (born 1934) and his colleagues at SEMA, a consulting company. A team at SEMA was working on the concrete, multiple criteria, real-world problem of how firms chose among possible new activities. They had encountered problems using weighted sums. Bernard Roy, who had a background in graph theory, was called in as a consultant and the group developed the original ELECTRE method. As it was first applied in 1965, the ELECTRE method was to help choose the best action(s) from a given set of actions, but it was soon applied to problems of ranking and sorting as well. The method became more widely known when a paper titled “La méthode ELECTRE” by Bernard Roy appeared in a French operations research journal Revue d’Informatique et de Recherche Opérationelle in 1968. It evolved into ELECTRE I and the evolutions have continued with ELECTRE II, ELECTRE III, ELECTRE IV, ELECTRE IS and ELECTRE TRI. Bernard Roy is widely recognized as the father of the ELECTRE method, which was one of the earliest approaches in what is sometimes known as the French School of decision making. It is usually classified as an “outranking method” of decision making.

Origins of Multiple Objective Mathematical Programming It is hard to speak about the roots of multiple objective mathematical programming without recognizing George Dantzig’s (1914–2005) contributions to linear programming. The history of linear programming is fascinating. In 1947, George Dantzig proposed the simplex algorithm as an efficient method for solving linear programming problems (see Dantzig, 1948). He was then working in the SCOOP program (Scientific

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(Left) George Dantzig (Right) Leonid Vitaliyevich Kantorovich Courtesy: Wikimedia Commons, http://en.wikipedia.org/wiki/Leonid_Kantorovich.

Computation of Optimum Programs), a US government research program, seeking to make the war time logistics operations more efficient. In the Soviet Union, Leonid Kantorovich (1912–1986) had earlier proposed a similar method for economic planning (Mathematical Methods of Organizing and Planning Production, 1939), unfortunately, his contribution remained unknown in the western world. Apparently, what made Dantzig’s (and Kantorovich’s) contributions so important was the simultaneous development of the digital computer, making it possible to use the simplex algorithm to solve real-world problems. Linear programming quickly became popular in industry. Saul Gass’s popular textbook, Linear Programming, published in 1958, helped applications to become more widespread. Several scholars pursued extensions of linear programming to (convex) nonlinear programming problems, notably Harold W. Kuhn (born 1925) and Albert W. Tucker (1905–1995). Their paper “Nonlinear Programming” in 1951 is a classic. See also G. Zoutendijk’s book, Methods of Feasible Directions, published in 1960. Mathematical programming had a problem: it was not suitable for solving problems with multiple objectives (per se). But early on, researchers realized that they could use weights to combine objectives into a composite or proxy objective. Accordingly,

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Harold W. Kuhn

Courtesy: Ron Gass.

Albert W. Tucker

mathematical programming provided a necessary foundation and framework for multiple objective mathematical programming. In the early 50s, Tjalling C. Koopmans (1910–1985), Nobel Prize winner in Economics in 1975, extended Pareto’s work introducing the notion of “efficient vector” in the context of a resource allocation problem, paving the way for multiple objective mathematical programming. See Koopmans’ “Analysis of Production as an Efficient Combination of Activities” published in 1951.

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Two influential papers by Saul Gass (born 1926) and Thomas Saaty (born 1926) dealing with the parametric objective function, published in Operations Research in 1954 and 1955, deserve to be mentioned. Their algorithm could be used for generating efficient solutions by varying the weights of a composite (aggregate) value function, a popular technique used in early multiple objective linear programming methods. In 1955, Abraham Charnes (1917–1992), William Cooper (born 1914), and R.O. Ferguson published an article “Optimal Estimation of Executive Compensation by Linear Programming” in Management Science that contained the essence of goal programming, even though the term goal programming was first used only in Charnes and Cooper’s book, Management Models and Industrial Applications of Linear Programming, in 1961. The idea of goal programming is simple; it is related to Simon’s level of aspiration concept. Ask the decision maker to specify target values for goals and formulate the problem as one of minimizing the weighted deviations from those target values. Alternatively, instead of weights, one could use a lexicographic (pre-emptive) model for the goals. In the original version, all constraint and goal functions were assumed linear. Hence goal programming could be regarded as a generalization of linear programming. At a conference organized by Mihajlo D. Mesarovic at the then Case Institute of Technology (now Case Western Reserve University) in 1963, Mesarovic presented Abraham Charnes and William W. Cooper with a poem that he wrote: Programming sticks upon the shoals Of incommensurate multiple goals, And where the tops are no one knows When all our peaks become plateaus The top is anything we think When measuring makes the mountain shrink. The upshot is, we cannot tailor Policy by a single scalar, Unless we know the priceless price Of Honor, Justice, Pride, and Vice. This means a crisis is arising For simple-minded maximizing.

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The poem was published in M.D. Mesarovic, Views on General Systems Theory, in 1964. Numerous researchers were stimulated by Abraham Charnes and William Cooper’s work. In fact, goal programming has seen a steady stream of research publications. Among the early contributors were Bruno Contini (born 1936) and Stanley Zionts (born 1937) (both of whom studied with Cooper), who developed a multiple criteria negotiation model (“Restricted Bargaining for Organizations with Multiple Objectives”) which they published in 1968. Zionts, whose background was in Operations Research, specifically linear and integer programming, applied a variation of this approach to a problem of steel allocation in India. Other influential publications on goal programming were Yuji Ijiri’s Management Goals and Accounting for Control in 1965 and Sang Lee’s Goal Programming for Decision Analysis in 1972. Arthur M. Geoffrion (born 1937) published two important articles in the late 1960s, helping to lay the theoretical foundation for multiple objective mathematical programming. The first was about solving bi-criteria mathematical programs; it was published in Operations Research in 1967. The paper showed in detail how to generate the efficient frontier for the case of two objectives. The second paper developed the concept of “proper efficiency” and the theory of vector maximization. It was published in the Journal of Mathematical Analysis and Applications in 1968. This paper provided a redefinition of the fundamental concept of efficiency to eliminate certain anomalous situations. The definition of proper efficiency avoided some of the drawbacks inherent in the earlier definitions. A comprehensive theory of vector maximization was constructed using the new definition. Several scholars addressed vector-valued criteria in automatic or optimal control. One of the first was Lotfi A. Zadeh’s (born 1921) short paper “Optimality and Non-Scalar-Valued Performance Criteria” published in IEEE Transactions on Automatic Control in 1963. He writes: One of the most serious weaknesses of the current theories of optimal control is that they are predicated on the assumption that the performance of a system can be measured by a single number … The trouble with this concept of optimality is that, in general, there is more than one

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Lotfi Zadeh

consideration that enters into the assessment of performance of S (the system) and in most cases these considerations cannot be subsumed under a single scalar-valued criterion.

See also Klinger’s paper on vector-valued performance criteria, published in the same journal the following year, providing a response to Zadeh’s original paper, as well as Da Cunha and Polak’s paper “Constrained Minimization under Vector-Valued Criteria in Finite Dimensional Spaces” published in 1967. Elements which belong to the Pareto-optimal set can be found by solving a family of standard optimal control problems, using a weighted sum of individual criteria of the controllers. Several of the (modern) MCDM scholars had a background in optimal control, for example, Oleg Larichev, Andrzej Wierzbicki, Po-Lung Yu, Masatoshi Sakawa, and Raimo P. Hämäläinen. In their early work, one can clearly see this influence. Lotfi Zadeh also made an original contribution to what became to be known as robustness analysis by inventing fuzzy set theory. Many MCDM scholars followed in Zadeh’s footsteps by suggesting Fuzzy MCDM techniques. The original paper was titled “Fuzzy Sets” and was published in 1965. Zadeh’s fuzzy set theory or fuzzy logic has found widespread applications. It has been applied to diverse fields, from control theory to artificial intelligence, yet still remains controversial among many scientists.

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Chapter 2

MCDM Developments in the 1970s

The 1970s saw many seminal contributions in the theory and method development of multiple criteria decision making, including the publication of Ralph Keeney and Howard Raiffa’s book on multiattribute utility theory (1976) and Jared Cohon’s book on multiobjective programming and planning (1978). Many important interactive mathematical programming methods were developed (Benayoun, et al., 1971; Geoffrion, Dyer and Feinberg, 1972; and Zionts and Wallenius, 1976). Vector optimization also advanced, notably by the efforts of Ralph E. Steuer. Bernard Roy advanced the field by developing different versions of ELECTRE methods and by establishing the European Working Group on Multiple Criteria Decision Aid (MCDA), which will have its 74th meeting in October 2011! Po-Lung Yu and Milan Zeleny advanced the field with theory and method development. Toward the end of the decade, Andrzej Wierzbicki developed the concept of achievement scalarizing function. Thomas L. Saaty published the first version of his celebrated work on the Analytic Hierarchy Process in the late 70s. The 1970s was a decade of theory and method development, although many of us had a keen interest in applying our work in practice. We had high hopes that our methods would be applied by companies and public organizations. Methods were often programmed in FORTRAN (or APL) for mainframe computers, but could be used interactively using time-sharing via teletypes. Computer graphics were not available at the time. The first MCDM Conference and the formation of the Special Interest Group on Multiple Criteria Decision Making took place in 1975, even though an earlier conference was organized by Milan Zeleny at the

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University of South Carolina in 1972. The Special Interest Group became the International Society on Multiple Criteria Decision Making in 1998. The field was small and had not yet become fragmented into different schools of thought. The concept of an outranking relation developed by Bernard Roy has been central to many methods he and his colleagues developed over the years. Roy’s ELECTRE method was, over the years, followed by a family of ELECTRE methods (ELECTRE II, III, and IV). In his efforts to establish the French School on MCDA, Bernard Roy was joined by several prominent Belgian and French colleagues, such as Philippe Vincke, Jean-Pierre Brans, Eric Jacquet Lagreze, Marc Pirlot, Marc Roubens, Jacques Teghem, Vincent Mousseau, Daniel Vanderpooten, and Denis Bouyssou. For early review papers, see Bernard Roy’s 1971 paper and B. Roy, Ph. Vincke, and J.P. Brans, “Aide à la décision multicritère,” Revue Belge de Statistique, 1975. References to ELECTRE II and III are, Bernard Roy and Patrice Bertier, 1973, and Bernard Roy, 1978, respectively. Based on a publication in Revue Metra in June 1970 (Progressive Orientation Procedure), R. Benayoun, J. deMontgolfier, J. Tergny, and O. Larichev published in 1971, the STEP-method for solving linear programming problems with multiple objectives. The method starts by optimizing each objective separately, to obtain the ideal solution to the problem. At each iteration, a linear programming (LP) problem is solved to obtain a feasible compromise solution, which is nearest in a MINIMAX sense to the ideal solution using normalized weights for the objective functions. (This feature bears some resemblance to the achievement scalarizing function developed by Wierzbicki a few years later.) Next, the decision maker must choose the criteria which he would be willing to worsen to allow for an improvement in criteria that are deemed to be unsatisfactory, and to specify the maximal amount of relaxation for each objective to be relaxed. At the next iteration the feasible region is modified accordingly. Arthur Geoffrion published a working paper at UCLA in September 1970 entitled “Vector Maximal Decomposition Programming.” This working paper formed the basis of the celebrated Geoffrion, Dyer, and Feinberg Management Science publication in 1972. Geoffrion essentially

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Arthur Geoffrion’s original working paper in 1970 on “Vector Maximal Decomposition Programming” leading to the Geoffrion-Dyer-Feinberg Management Science paper (1972).

proposed a man-machine interactive approach to the multiple criteria problem, where man-machine iterations would alternate before termination. It demonstrates that a large-step gradient algorithm could be used for solving the problem, if the decision maker were able to specify an overall implicit utility (value) function defined on the values of the objectives. The method never requires this function to be specified explicitly. Instead it only asks for local trade-off information from the decision maker to guide the search. The idea was theoretically elegant. The method was subsequently programmed for the computer by James Dyer (1973). James Dyer, at the 20th International Conference on MCDM in Chengdu, China, presented a plenary talk about the origins of the method.

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Following the traditions in optimal control, M.E. Salukvadze1 published three papers in Automation and Remote Control, two in 1971 and one in 1972, all of which are of historical significance. They represent one of the first attempts to employ the “ideal point” to scalarize problems having multiple objectives. Designed to solve control problems with multiple (vector) functionals, the method minimizes the Euclidean distance between the ideal trajectory and the set of feasible trajectories. No interaction with the decision maker takes place. Po-Lung Yu and George Leitmann criticized Salukvadze’s choice of the metric as arbitrary and presented a more general metric in a JOTA 1974 publication. Another important early Soviet paper was A. Lotov’s “Numerical Method of Constructing Attainability Sets for a Linear Control System,” published in 1972. This paper essentially laid the foundation for Lotov’s reachable set method, which made projections of the constraint set onto the subspace of objective functions. The method relies on the theory of linear inequalities to generate the projections. V.A. Bushenkov and A. Lotov provided extensions and extensively published on the idea in the 80s. Ralph E. Steuer published his first paper jointly with his thesis supervisor James Evans, in Mathematical Programming (Evans and Steuer, 1973). The title of the paper was “A Revised Simplex Method for Linear Multiple Objective Programs.” For linear multiple objective problems, a necessary and sufficient condition for a point to be efficient was employed to develop a revised simplex algorithm for the enumeration of all efficient extreme points. The algorithm was the first of its kind. Several options within this algorithm were tested on a variety of problems. This was followed by the development of the ADBASE program to generate all 1

For interesting papers on Soviet research on MCDM, see V.M. Ozernoy’s survey article published in 1988, E. Lieberman’s overview in Management Science in 1991, and E. Lieberman’s book published in 1991. The publications review Soviet MCDM research since 1971. Theoretical methodology research dominated the Soviet literature. Interestingly, the interactive approaches seemed most popular. The overall focus was on solving “difficult” problems (with irregular feasible regions) commonly found in engineering. Several of the approaches bear semblance to approaches presented in the west, although there were also distinctively different ideas. We mention what we believe to be the most innovative ideas. Stancu-Minasian compiled a bibliography of 421 selected works related to MCDM in 1975.

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efficient extreme point solutions for multiple objective linear programming problems in 1975.2 The following year, Steuer published a method in Management Science based on the idea of using intervals for weights, rather than fixed weights, paving the way for much later research along similar lines. Isermann developed an algorithm to generate all efficient solutions for a linear multiple objective program in a paper published in Operational Research Quarterly in 1977. During the 70s, Ralph Steuer extensively collaborated with Jonathan Kornbluth. One outcome of their joint work is their 1981 paper on multiple objective linear fractional programming (Kornbluth and Steuer, 1981). Milan Zeleny, a student of Po-LungYu at the University of Rochester, independently carried out and published work similar to Ralph Steuer’s. Yu and Zeleny published, among others, two significant papers, the first in the Journal of Mathematical Analysis and Applications in 1975 and the second a year later in Management Science. The first paper effectively provides a method for generating the set of all nondominated solutions in linear cases. The second paper investigates some basic properties in the decomposition of the parametric space. The second paper is a geometric decomposition method bearing similarity to that presented by Tomas Gal and Josef Nedoma in their Management Science paper “Multiparametric Linear Programming” in 1972. An avid critic of the concept of optimization, Zeleny published the idea of generating compromise solutions via the method of the displaced ideal in Computers and Operations Research in 1974. Stanley Zionts and Jyrki Wallenius published their well known method for interactively optimizing problems with multiple objectives in 1976. They were influenced in their work by earlier research of Contini and Zionts. The original method was based on assuming a linear implicit underlying value function, but was extended to cover concave value functions in 1983. One of their early ideas explored the possibility of modifying the right-hand-side of the constraints (objectives). They, however, quickly abandoned that line of thinking. In order to achieve convergence, it proved better to keep the constraint polyhedron fixed and 2

Günter Fandel published an interesting paper in 1975, discussing solution principles for vector maximum problems (Fandel, 1975).

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Stan and Terri Zionts, Brussels 1974, when Stan was a faculty member at the European Institute for Advanced Studies in Management.

Jyrki Wallenius just before defending his doctoral dissertation, Helsinki School of Economics, September 19, 1975 (from front to rear: candidate Wallenius, chairman Rector Jaakko Honko, opponent Bertil Näslund of the Stockholm School of Economics).

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have the decision maker move along the efficient surface of that polyhedron via iteratively solving a so-called “lambda problem.”3 Before the ideas took shape, they also explored what they called a naive method, where the decision maker would simply move from one efficient extreme point solution to another. For large scale problems, which Zionts and Wallenius had in mind, this would, however, take an eternity. Hence it was important to make the algorithm efficient in terms of numbers of questions asked. Part of the algorithm was the “efficiency routine” to test for adjacent efficient solutions, which the authors published separately in Operations Research in 1980. Along with the Geoffrion, Dyer and Feinberg method, it became a standard reference. They started a stream of research in interactive multiple objective mathematical programming that is still popular today. Their first working paper was called “A SimplexType Interactive Programming Method for Solving the Multiple Criteria Problem,” October 1973 (EIASM Working Paper #44), emphasizing the fundamental idea of extending the simplex method to multiple objective linear programming. The authors were hopeful that companies would start using their method, since many of them already used linear programming, and it would be a relatively small step to extend it to multiple objective linear programming. The real world was, however, not that simple! Ralph Keeney and Howard Raiffa published their book “Decisions with Multiple Objectives: Preferences and Value Tradeoffs” in 1976. According to the authors, they worked on the book for about six years. The book summarized much of the authors’ research dating from 1968 to 1975. An important paper (covered in their book) was Keeney’s Management Science paper published in 1972, discussing utility functions for multiattributed consequences. The Keeney–Raiffa book was instrumental in establishing the theory of multiattribute value and utility measurement as a discipline. It became a standard reference and textbook for many generations of graduate students in decision analysis and MCDM. In a thorough treatment, they covered trade-offs under certainty and under uncertainty, both the two-attribute and the n-attribute cases. They also included a chapter on the (now) classic application concerning 3

The idea of the “lambda problem” has been applied numerous times in different contexts. A recent application is to internet search. See Asim Roy et al. (2008).

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Inside cover of R. Keeney and H. Raiffa’s 1976 book.

the airport development options for Mexico City, originally published by de Neufville and Keeney in 1974. Keeney and Raiffa finished their book while at IIASA in Laxenburg, Austria. As the authors state, “this is a big book and not all of it has to be read!” Interestingly, their 1976 book contained the rudiments of a sequel by Ralph Keeney in 1992 called Value Focused Thinking. Lawrence D. Phillips and Detlof von Winterfeldt have reflected on the contributions of Ward Edwards to decision research after Edwards’ death (Advances in Decision Analysis, edited by Ward Edwards, Ralph F. Miles Jr., and Detlof von Winterfeldt, 2007). Ward Edwards apparently liked multiattribute utility theory. However, he thought that the Keeney and Raiffa approach was too difficult to use in practice. Accordingly, he created a simpler version of this method — which later came to be known as SMART — the simple multiattribute rating technique, which he published in two papers (1971; 1977). The SMART method attracted many

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followers and is still being used. In fact, Ward Edwards developed several versions of SMART and applied them to social problems. One quite remarkable application was an evaluation of school desegregation plans for the Los Angeles Unified School District. Peter Fishburn made many fundamental contributions to the theory of social choice and utility theory. During the 70s and 80s, he continued his research on utility theory, at times dealing with two-attribute and multiattribute situations. During the 1980s, Peter Fishburn published several books, including The Foundations of Expected Utility (1982) and Nonlinear Preference and Utility Theory (1988). Many of his contributions are fundamental and embedded in multiattribute utility theory, such as his research on lexicographic preferences, independent preferences, and nonlinear preferences. As mentioned in the citation of his John von Neumann Theory Prize, Fishburn has also made significant contributions to group decision making, including decisions based on voting processes. Some of these contributions can be found in his book, The Theory of Social Choice (1973), as well as the numerous articles on social choice functions, majority choice, and Arrow’s impossibility theorem. Andrzej Wierzbicki, a Polish mathematician with a background in optimal control theory, published the first two papers dealing with the achievement scalarizing function in 1975 and 1977. The 1979 Königswinter Conference Proceedings paper from 1980 reviews his early thoughts. In subsequent papers, Wierzbicki further extended and refined his ideas. The use of the achievement scalarizing function effectively means optimization of a “value function,” which is defined in terms of a reference point given by the decision maker. This is not equivalent to minimizing the distance (or a norm) to the reference point, commonly used in goal programming. A remarkable feature of the achievement scalarizing function is that it can be used to project both infeasible and feasible points to the efficient frontier. By adding an auxiliary term to the achievement scalarizing function, one can avoid the generation of inefficient solutions among the set of so-called weakly efficient solutions. Furthermore, it is possible to generate any efficient solution by formulating an appropriate achievement scalarizing function. The definition of the achievement scalarizing function was a breakthrough and its use has become commonplace in interactive methods. Wierzbicki was active in developing

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computerized decision support systems based on the idea of the achievement scalarizing function. Jared Cohon and Yacov Haimes independently pioneered applications of MCDM models to water resource management. J.L. Cohon and D.H. Marks published a paper “Multiobjective Screening Models and Water Resource Investment” in 1973. Environment and sustainable development reflected the interests of Jared Cohon, while serving as Dean of the School of Forestry and Environmental Studies at Yale University. Moreover, Jared Cohon published a significant book, Multiobjective Programming and Planning by Academic Press in 1978, taking a broad view of multiple objective programming, yet emphasizing the methods most useful for continuous problems. Y. Haimes and W. Hall published in 1974, a paper developing the surrogate worth trade-off method, applied to water resource management. Y. Haimes, W. Hall and H. Friedman published a book dealing with multiobjective optimization in water resources systems in 1975. According to Forman and Gass, Thomas L. Saaty, while teaching at the Wharton School in the 70s, was troubled by the communication difficulties he had observed between the scientists and lawyers concerning priority setting and decision making (Forman and Gass, 2001). Saaty was motivated to develop a simple way to help lay people make complex decisions. The result was the analytic hierarchy process (AHP). The first publications appeared in 1977 (“A Scaling Method for Priorities in Hierarchical Structures,” Journal of Mathematical Psychology; and “The Sudan Transport Study,” Interfaces). His first book on the AHP was published by McGraw Hill in 1980 with the title Analytic Hierarchy Process. According to Saaty, AHP is a method to derive ratio scales from pair-wise comparisons. The input can be obtained from objective measurements such as prices, weights etc., or from subjective measurements such as feelings and preferences. AHP allows some inconsistency in judgments. The degree of inconsistency is reported by an inconsistency index. The weights are derived from the principal eigenvectors. Over a period of 30 years, the AHP has become one of the most celebrated MCDM tools for practitioners. It is being widely used by corporations and governments all over the world. Several commercial software implementations exist, the first being EXPERT CHOICE, originally developed in 1983.

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James Dyer and Rakesh Sarin published “The Measurable Multiattribute Value Function” paper in Operations Research in 1979. Such functions are based on the concept of a “preference difference” between alternatives and provide an interval scale of measurement for preferences under certainty. The authors present conditions for additive, multiplicative, and more complex forms of the measurable multiattribute value function. Building on earlier ideas of Farrell and developed in Rhodes’ doctoral dissertation, data envelopment analysis (DEA) was developed by A. Charnes, W.W. Cooper and E. Rhodes in their EJOR article “Measuring the Efficiency of Decision Making Units” in 1978. During the 70s, conjoint analysis received attention as an approach to measuring consumers’ trade-offs among products and services possessing multiple attributes. The focus was on explaining and predicting consumer choices rather than aiding consumers in their choice problems. The models were often referred to as “attitude models.” See P. Green and V.R. Rao’s review paper on conjoint analysis in 1971, V. Srinivasan and A.D. Shocker’s paper dealing with the weight estimation problem (Srinivasan and Shocker, 1973b), and the paper by W. Wilkie and E. Pessemier about multiattribute attitude models in 1973. The reader is also referred to the interesting linear programming-based technique for preference analysis by Srinivasan and Shocker (1973a). In 1979, Daniel Kahneman and Amos Tversky published their celebrated prospect theory paper, as an alternative to the expected utility model. Prospect theory could explain many of the paradoxes of the classical utility theory, among others, the famous Allais paradox. One of the key ideas was that people make choices with respect to a reference point. They consider gains and losses with respect to such a reference point. Moreover, people react more strongly to negative than to positive stimuli of the same magnitude, exhibiting loss aversion. The original model was extended to riskless choice in Tversky and Kahneman (1991).4 Although 4

Independently from Tversky and Kahneman, Pekka Korhonen, Herbert Moskowitz and Jyrki Wallenius considered the application of prospect theory to riskless choice in their Annals of Operations Research paper in 1990. Their first versions date back to 1986 and 1987. See Korhonen, Moskowitz, and Wallenius (1992).

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(Left) Daniel Kahneman Courtesy: Wikimedia Commons, http://en.wikipedia.org/wiki/List_of_Nobel_laureates_in_Economics.

(Right) Amos Tversky

intended as a descriptive model of choice, the key ideas have been applied to normative MCDM models. Daniel Kahneman received the Nobel Prize in Economics in 2002 for his contributions to the psychology of economics. Amos Tversky died six years earlier; otherwise he would almost certainly have shared the prize with Kahneman. Po-Lung Yu published the fundamental ideas of his habitual domain theory in the Königswinter Conference Proceedings in 1980. The paper was based on a 1979 working paper, which he wrote at the School of Business, University of Kansas. Yu argues that people develop a fairly stable set of ways of thinking and making judgments, which he calls a habitual domain. The theory essentially integrates findings from psychology, mathematics, and common sense. Yu discusses the formation of habitual domains and how one can expand one’s habitual domain. The paper concludes by discussing some applications. According to the author, a number of state variables are used to describe human physiological conditions, the social situation, and individual’s goals. Their values are constantly monitored. When the current value falls significantly below its goal value, a “charge” (tension) is produced. The purpose of “attention” is

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From left: Milan Zeleny, Po-Lung Yu, and Jonathan Kornbluth at the Manchester Conference, 1988.

Po-Lung Yu and Herb Moskowitz, Helsinki, 1988. They gave joint talks on Habitual Domains. Moskowitz is Distinguished Professor Emeritus at Purdue University.

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to release the “charges” efficiently. Over thirty years, Po-Lung Yu has extensively written about his ideas related to “Habitual Domains” and presented seminars to business people about how they can expand their habitual domains. Po-Lung’s ideas have found widespread acceptance, particularly in Asia. Forming Winning Strategies: An Integrated Theory of Habitual Domains, published by Springer in 1990, is a popular book. Po-Lung Yu has also given many tutorial presentations in scientific conferences about “Habitual Domains.” Younger audiences associate Po-Lung Yu’s name with “Habitual Domains,” forgetting his past in optimal control and game theory.

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Chapter 3

MCDM Developments in the 1980s

The MCDM field matured during the 1980s. Many important books were published covering developments in MCDM.1 We highlight several of the books here. Steuer’s book Multiple Criteria Optimization provided an influential coverage of multiobjective mathematical programming techniques. Von Winterfeldt and Edwards’ excellent book Decision Analysis and Behavioral Research has not yet had a desired impact on multiple criteria research, despite calls for additional behavioral realism in models by several scholars. Spronk’s book Interactive Multiple Goal Programming was one of the earliest to draw attention to applications of MCDM models in finance. Zeleny’s book Multiple Criteria Decision Making provided a broad coverage of the field, always in search of new paradigms. Saaty, in his 1980 book, focused on his newly developed analytic hierarchy process (AHP) methodology, which continued to thrive during the 1980s and beyond. Review articles on MCDM began to appear2: Roy and Vincke, and later Roy and Vanderpooten, covered developments of the French school. 1

Saaty, The Analytic Hierarchy Process, 1980; Spronk, Interactive Multiple Goal Programming, 1981; Zeleny, Multiple Criteria Decision Making, 1982; Goicoechea, Hansen, and Duckstein, Multiobjective Decision Analysis with Engineering and Business Applications, 1982; Chankong and Haimes, Multiobjective Decision Making: Theory and Methodology, 1983; Sawaragi, Nakayama, and Tanino, Theory of Multiobjective Optimization, 1985; Yu, Multiple Criteria Decision Making, 1985; Steuer, Multiple Criteria Optimization, 1986; von Winterfeldt and Edwards, Decision Analysis and Behavioral Research, 1986; and Vincke, Multicriteria Decision-Aid, 1992. 2 Roy and Vincke, EJOR, 1981; Roy and Vanderpooten, JMCDA, 1996; Farquhar, 1983; Evans, Man. Sci., 1984; Romero, EJOR, 1986; Ozernoy, NRL, 1988; Aksoy, Man. Res. News, 1990; Lieberman, Man. Sci., 1991; Shin and Ravindran, EJOR, 1992; Stewart, OMEGA, 1992; Dyer et al., Man. Sci. 1992. 31

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Cover of Ralph Steuer’s book published in 1986.

Farquhar covered advances in utility assessment methods. Evans discussed multiple objective mathematical programming. Ozernoy and Lieberman covered Soviet research through the 1980s. Much of this body of research had been unknown to Western scholars until then. Romero covered extensions of goal programming. Shin and Ravindran reviewed interactive methods, with a particular emphasis on different interaction styles. Dyer et al. provided predictions into the future. Issue 11 of Management Science in 1984, edited by Jaap Spronk and Stanley Zionts, was devoted to Multiple Criteria Decision Making articles. There were other special issues of journals as well. International conferences continued on a regular basis with increasing participation both in the total number of participants and the number of countries represented. The pioneers of MCDM had the vision of internationalizing the field and they were successful in rapidly achieving this

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The first issue of FACET (July 1983) edited by Stan Zionts.

goal. Stan Zionts prepared and distributed a newsletter, FACET, in the early years. Ralph Steuer took over the newsletter and renamed it WorldScan. During the late 1980s, WorldScan was distributed to over 1000 members of the Society in more than 50 countries.

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The first issue of MCDM WorldScan (February 1987) edited by Ralph Steuer.

The development of new interactive approaches continued for the continuous-solution-space problems and the research on interactive approaches for discrete-alternative problems made a strong start during this decade. Parallel to the developments in personal computers and

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computer graphics, several researchers focused on developing visual interactive decision support systems. The developments in fuzzy set theory initiated related multiple criteria research on approaches during this decade, and this became one of the fastest growing areas. Another area that enjoyed rapid growth during this and later decades was data envelopment analysis originally developed by Charnes, Cooper and Rhodes (EJOR, 1978). However, not until later were the connections to MCDM explored. In addition to methodological developments, scholars pursued significant applications of MCDM models to practice. These include Jaap Spronk (financial modeling), Carlos Romero (agriculture), Theodor Stewart and Raimo Hämäläinen (environmental problems), and Benjamin Hobbs (energy). We cite Romero and Rehman’s Multiple Criteria Analysis for Agricultural Decisions book that was published later, in 2003. Group-decision-making problems were also studied by MCDM scholars who wanted to apply MCDM tools in one form or another to solve group-decision problems. Howard Raiffa was a leading researcher in group-decision-making and he is the author of the book The Art and Science of Negotiation published in 1982.

Interactive Approaches Researchers continued developing interactive approaches for the continuoussolution-space problems during the 1980s. Zionts and Wallenius (Man. Sci., 1983) extended their 1976 method to handle a class of underlying nonlinear utility functions. Steuer and Choo (Math. Prog., 1983) developed an approach using a weighted Tchebycheff function that facilitates reaching any efficient solution. They used the preference information obtained from a decision maker (DM) to restrict the weights and converge to a preferred solution. Nakayama and Sawaragi (1984) developed the satisficing trade-off method. Korhonen and Laakso3 (EJOR, 1986) utilized Wierzbicki’s achievement scalarizing function to generate all efficient 3

Jukka Laakso was a gifted graduate student of Pekka Korhonen at the Helsinki School of Economics in the 1980s. Unfortunately, he died before he was able to complete his dissertation.

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solutions along a chosen direction by parametrically moving in that direction. They present solutions graphically in the criterion space and ask the DM to choose the best. The DM may search further by changing the direction until a satisfactory solution is found. Korhonen and Wallenius (NRL, 1988) implemented a free search version of the Korhonen-Laakso algorithm where the DM can search the solutions on the nondominated frontier. At any point, the DM can decide which part of the frontier to explore, changing direction or step size whenever she chooses. The authors called the search “Pareto Race,” implying a race in a preferred direction along the Pareto frontier. The search is supported by computer graphics to aid the DM visually. For entertainment and to satisfy their curiosity, the authors organized a competition to find the fastest “Pareto Race driver” at the Manchester MCDM Conference in 1988. A target solution was given in the criterion space and the competitors tried to reach the point as fast as possible. Murat Köksalan and Vahid Lotfi were tied as the fastest drivers and both won a free copy of the software. Many interactive approaches developed for discrete-alternative problems had structures that were similar to their continuous counterparts. Some assumed that the DM has an underlying unknown utility function of a certain form. Such methods require the DM to compare chosen pairs of alternatives at certain points during the solution process. Utilizing the DM-obtained preference information together with the properties of the assumed form of the DM’s utility function, they reduce the set of candidate solutions for the most preferred solution. The process is continued until the most preferred solution is identified. Keeping the preference information requirement from the DM at a reasonable level is a main concern for these approaches. In general, for a simpler form of utility function, information obtained from a DM becomes more effective in reducing the solution space and less information is required from the DM to converge to a most preferred solution. On the other hand, a simpler form of utility function might be less representative of reality in capturing preferences of DMs. Clearly there is a trade-off between these two approaches. A pioneering interactive approach for discrete-alternative multiple criteria problems was developed by Stanley Zionts and published in EJOR in 1981. This approach was an adaptation of the Zionts-Wallenius

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method (1976) to the discrete-alternative problems. Zionts assumed an underlying linear utility function. He required the DM to compare an incumbent nondominated alternative to the adjacent nondominated alternatives of the convex set of alternatives. The algorithm stopped when an incumbent alternative was preferred to all the adjacent nondominated solutions of the convex set of alternatives. A new incumbent was generated whenever the old incumbent was found inferior to some other (adjacent efficient) alternative. Later, Korhonen, Wallenius, and Zionts (Man. Sci., 1984) developed a more general approach assuming an underlying quasiconcave utility function. They constructed convex cones, utilizing preference information obtained from the DM, together with the properties of quasiconcave functions. They proved that any solution in these cones or dominated by these cones cannot be a candidate for the most preferred solution. The algorithm stops when all alternatives are proved to be less preferred than an incumbent. Köksalan, Karwan, and Zionts (IEEE Trans. on SMC, 1984) also worked on the quasiconcave utility function case, focusing on keeping the information required of the DM to a minimum. They created dummy alternatives and devised procedures so that the resulting cones were more powerful in eliminating inferior solutions than the original procedure. As quasiconcave utility functions (which correspond to indifference curves convex to the origin) are considered to represent human preferences well in general, many other authors have also developed approaches for this case (see, for example, Malakooti, IEEE Trans. on SMC, 1989, and the book by D. Olson, Decision Aids for Selection Problems, 1996). Later, Köksalan and Sagala (Man. Sci., 1995a) further generalized the interactive approaches by developing an approach that works for any utility function so long as the DM’s preferences are monotone in each criterion. Stewart (Man. Sci., 1993) conducted experiments to test the effects of modeling assumptions and parameters of interactive approaches on the efficient use of the DM’s judgments and on the robustness to judgment errors. Some approaches took advantage of the developments in personal computers and computer graphics to help DMs visually obtain preference information from them. Lotov was a pioneer in developing visualization techniques for MCDM. Much of his research with colleagues has been summarized in the following two books: Lotov, Bushenkov, and

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A newspaper clipping on applying a multiple criteria decision support tool to house purchase decisions, Buffalo News, NY 1983.

Kamenev, Interactive Decision Maps, Approximation and Visualization of the Pareto Frontier, 2004; Lotov and Pospelova, Multiobjective Decision Making, published in Russian in 2008. Korhonen (EJOR, 1988) developed a visual interactive approach (VIMDA) for discrete alternative problems using computer graphics that presented alternatives to the DM for comparison purposes. No assumptions regarding the DM’s underlying utility function were postulated. VIMDA has been updated to solve

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large-scale problems that have millions of alternatives. Another visual interactive approach, called visual interactive sensitivity analysis (VISA), was developed by Belton and Vickers (1989). The approach uses a simple additive utility function to aid the DM to perform sensitivity analyses using graphics. As many interactive approaches assumed different utility function forms and utilized their properties in converging to the preferred solutions, it is important to know what type of a utility function represents the preferences of a specific DM. Salminen, Korhonen, and Wallenius (JORS, 1989) developed a procedure to identify the form of a DM’s utility function based on the DM’s preferences on pairs of presented alternatives. Later, Köksalan and Sagala (JMCDA, 1995b) developed an effective procedure that identifies a DM’s utility function form after asking a small number of pairwise comparisons. Once the form of the utility function is identified, the algorithm most suitable for that form may be used to find the most preferred solutions. The preference information obtained in identifying the form of the utility function may also be used in finding the preferred solutions. Pioneering multi-criteria integer programming approaches were also developed in the late 1970s and 1980s (see, for example, Bitran, Math. Prog., 1977, Villareal and Karwan, Math. Prog., 1981, and Ramesh, Zionts, and Karwan, EJOR, 1986). The approaches were based on branchand-bound principles.

Multiattribute Utility Theory and Risk Much of the original multiattribute utility theory was developed by Ralph Keeney, Howard Raiffa and others during the 1970s. Keeney pursued applications during the 1980s, alone and together with von Winterfeldt and others. We cite some examples: A site evaluation study for nuclear waste disposal by Merkhofer and Keeney, published in Risk Analysis in 1987, and a study on value eliciting for complex policy decisions by Keeney, von Winterfeldt, and Eppel, published in Management Science in 1990. Ranking with partial information was the topic of Craig Kirkwood and Rakesh Sarin’s 1985 Operations Research paper. They applied their

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method to a problem of nuclear waste containment. Modeling partial or incomplete information has subsequently become a popular research topic. See, for example, Martin Weber’s paper in EJOR in 1987. David Bell published several papers on decision regret during the 1980s. Extensively cited is his article published in Operations Research in 1982. The idea is that DMs may experience feelings of regret or rejoicing (after the decision), which they want to incorporate into their decision making activity. David Bell developed his regret theory independently but simultaneously with two economists, G. Loomes and R. Sugden (see their article in Economic Journal, 1982, generalizing the simple concept of minimizing maximum regret in a decision situation).

Fuzzy Set-Based Approaches Fuzzy set theory, originally developed by Lotfi Zadeh, penetrated MCDM research towards the end of the 1970s and became popular. An early paper by Zimmermann (Fuzzy Sets and Systems, 1978) provided a linear programming formulation combining multiple objectives with fuzzy operators. This paper had an important impact on subsequent research in this area. It has been cited about 1000 times based on Google Scholar. Incidentally, Köksalan (1980) proposed a variation of this formulation in his Master’s thesis at the Middle East Technical University and applied it to a manpower planning problem of an academic department. R. R. Yager is another pioneering researcher in fuzzy multi-criteria decision making (see Yager 1982a, 1982b, Journal of Fuzzy Mathematics). His 1988 paper that appeared in IEEE Transactions on SMC had a large impact on this area and had over 1000 citations by the year 2009 from the articles in the ISI Database. This and several of his other papers focused on so-called ordered weighted averaging (OWA) operators. The OWA operators provide a parameterized class of average aggregation operators. Many such operators (for example, the arithmetic mean and median, as well as max and min operators) belong to this class. They have found widespread applications in different fields and particularly in computational intelligence. Hannan (Fuzzy Sets and Systems, 1981), Carlsson and Korhonen (Fuzzy Sets and Systems, 1986), Sakawa (Int. J. Man Machine Systems, 1983), and Sakawa et al. (IEEE Trans. on SMC, 1987) further

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developed approaches incorporating fuzzy logic to multiple criteria decision making and optimization. Their focus in the 1980s was on developing interactive approaches for fuzzy multiobjective problems. Research in fuzzy multi-criteria decision making in later decades continued and found many application areas in different fields. We mention in particular, the 1993 book by Sakawa entitled Fuzzy Sets and Interactive Multiobjective Optimization. Gwo-Hsiung Tzeng and his colleagues applied fuzzy multiobjective approaches to a variety of problems over the years (see, for example, Opricovic and Tzeng, Natural Hazards Review, 2003 and Hsieh et al. Int. J. Project Management, 2004). Besides fuzzy multi-criteria decision making, robustness considerations in modeling preferences started to receive attention. Examples are A. Arbel (EJOR, 1989) and A. Salo and R. Hämäläinen (Operations Research, 1992).

Other Approaches Saaty’s AHP methodology was on its way to become one of the most widely used tools in our field. AHP meetings have been held in several countries, including the US and China. During the 1980s, Saaty and his colleagues (notably Luis Vargas and Ernest Forman) pursued various applications in such fields as government, business, industry, healthcare, and education. During the 1980s, besides pursuing applications, Saaty also developed the axiomatic foundations of the AHP in a Management Science paper in 1986. His 1977 paper, “A scaling method for priorities in hierarchical structures,” published in the Journal of Mathematical Psychology, is one of the most widely cited papers in our field, with close to 1000 ISI citations. Harker and Vargas’ Management Science paper in 1987 has also been influential. The developments in methods based on outranking relations continued during the 1980s and later decades as well. The PROMETHEE method developed by Brans, Vincke, and Mareschal (EJOR, 1986) has been one of the popular methods in this area and has initiated further research over the years. The UTA method of Jacquet-Lagreze and Siskos (EJOR, 1982) estimates an additive utility function using information derived from the

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ranking of a set of alternatives by the DM. The ideas developed in this paper led to new methods and applications in later years. This method was included in the collection of the 30 most influential papers published in EJOR over its 30-year history, along with the Korhonen-Laakso (1986) reference direction method. The MACBETH approach was developed by Carlos Bana e Costa in his Ph.D. thesis in 1992. MACBETH is short for Measuring Attractiveness by a Categorical Based Evaluation Technique. For details, see Bana e Costa, De Corte, and Vansnick (2005). Goal programming was further developed by Carlos Romero, James Ignizio, Sang Moon Lee, and others. Two books by Ignizio are noteworthy: Goal programming and Extensions, 1976 and Linear Programming in Single and Multiple-objective Systems, 1982. Moreover, Carlos Romero and Tahir Rehman pursued goal programming applications to solving agricultural problems (Journal of Agricultural Economics, 1984). The first multiple objective genetic algorithm was developed by J.D. Schaffer in his doctoral dissertation (Vanderbilt University, Nashville) in 1984. He called his algorithm the vector evaluated genetic algorithm (VEGA). VEGA was a direct extension of single objective genetic algorithms. VEGA divided the population into subpopulations and evaluated each subpopulation with respect to a different objective in order to favor solutions that perform well with respect to different objectives. Schaffer’s pioneering work did not stimulate more research in multiobjective genetic algorithms for about a decade. The explosion in the amount of research in multiobjective genetic or evolutionary algorithms only began in the mid1990s and accelerated after 2000.

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Chapter 4

MCDM Developments in the 1990s and Beyond

The 1990s saw the continuing spread of ever more powerful personal computers. Many researchers began to talk about ubiquitous or pervasive computing. Spreadsheet models and spreadsheet solvers became popular. The 1990s also saw a rapid increase in the volume of MCDM publications. Essentially, the number of publications increased from 200 to 600 per year during that decade. What was happening? MCDM ideas and tools started to penetrate neighboring disciplines and various engineering fields, as well as medicine. There was the fear that engineers might not possess sufficient knowledge about the MCDM field, and would either reinvent the wheel or incorrectly apply MCDM tools. Often they would apply simple scoring models. The field was no longer small. In the 1970s and early 1980s, we had to do significant custom programming to apply MCDM models in practice. By the mid-90s, one could accomplish the same (and more) by using Visual Basic for Applications (VBA) programming in Excel (Kirkwood, 1997). Many important events occurred during the 1990s. They include the following1: 1. The World Wide Web was invented and its use became commonplace. The web has had a profound impact on our field. The first web-based MCDM decision support systems emerged in the mid-1990s.

1

For additional details, see Wallenius et al. (Man. Sci., 2008). 43

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2. Enhancements in computer graphics allowed for sophisticated and user-friendly interfaces. 3. MCDM models were to a larger extent applied in practice. Moreover, MCDM began to penetrate many new areas of research and applications, for example, data envelopment analysis, negotiation science, e-commerce, finance, engineering, and medicine. 4. The importance of MCDM was recognized in professional management journals, such as the Harvard Business Review and Fortune Magazine. 5. Data envelopment analysis (DEA) continued to grow in importance and its relationship with multiple objective linear programming (MOLP) was noticed. 6. In the mid-1990s, evolutionary multiobjective optimization (EMO) started to develop. 7. Multiobjective combinatorial optimization (MOCO) research started to become popular. We elaborate on several of the contributions below.

Evolutionary Multiobjective Optimization Despite significant progress, multiple criteria optimization techniques were unable to solve many highly nonlinear multiple criteria problems that had emerged, mostly in engineering. This generated the need for evolutionary multiobjective optimization (EMO). The basic idea of EMO is as follows. Start with an initial population. The evolutionary algorithm then improves the population by using stochastic procedures designed to mimic natural survival-of-the-fittest principles and genetic variation operators. The idea is to converge to a final population of points that approximates the nondominated set. From the publication of Schaffer’s doctoral dissertation in 1984, it took about 10 years before three working evolutionary algorithms were independently developed by three different groups of scholars: C. Fonseca and P. Fleming (multiobjective genetic algorithm, 1993), N. Srinivas and K. Deb (nondominated sorting genetic algorithm, 1994), and J. Horn, N. Nafploitis, and D. Goldberg (Pareto genetic

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algorithm,2 1994). These three algorithms spurred the growth of EMO. Other significant pieces of research from the same era include Carlos Fonseca’s Ph.D. thesis (University of Sheffield, 1995) and Eckart Zitzler’s Ph.D. thesis (ETH Zurich, 1999). Kalyanmoy Deb (jointly appointed by IIT, Kanpur and the Aalto University School of Economics), building upon the research of David Goldberg and John Holland, has become one of the leaders of the EMO community. The idea in early algorithms was to provide an approximation to the nondominated set. No user or decision maker was involved, in contrast to the customary approach in the MCDM field. The goal of the research, although using a very different technique, resembled the generation of all efficient extreme points for multiple objective linear programming problems. EMO, however, considered more complex problems than linear programming.

Mental Models and Problem Structuring Ralph Keeney wrote an influential book in 1992 entitled Value-Focused Thinking. In his book, he writes that “the standard way of thinking about decisions is backwards, people focus first on identifying alternatives rather than on articulating values. A problem arises and people react, placing the emphasis on mechanics and fixed choices instead of on the objectives that give decision making its meaning. [… This]

2 Interestingly, Sami Airo, who was one of Pekka Korhonen and Jyrki Wallenius’ Ph.D. students in the early 1990s at the Helsinki School of Economics, wrote a working paper “Approximating the Nondominated Set with the Simple Genetic Algorithm (SGA)” in 1994. He presented the paper at the ORSA/TIMS joint national meeting in Detroit, October 23–26, 1994. In the working paper, SGA was used to produce an approximation of the nondominated set in a multiple objective optimization problem. Different formulations for the fitness function were tested, such as ranking by nondominance and counting dominating criterion vectors. Interestingly, Sami concludes his working paper “In this way the SGA could be used as a part of a hybrid multiple criteria decision support tool. An even more interesting approach and an area for further research would be to enable DM to direct the SGA interactively towards the preferred part of the nondominated set.” Sami was a decade ahead of his time. Unfortunately, he never completed his doctorate; he was recruited to work for the Bank of Finland.

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shows how recognizing and articulating fundamental values can lead to the identification of decision opportunities and the creation of better alternatives.” The rudiments of “Value-Focused Thinking” may be found in Ralph Keeney and Howard Raiffa’s 1976 book which discuss “proxy attributes.” Problem structuring was a key focus by Abe Charnes and Bill Cooper in their early work in Management Science. The importance of problem structuring was forgotten, but resurrected in the 90s. In connection with the structuring of problems, the names of Ralph Keeney and Valerie Belton should be mentioned. Keeney’s focus was on structuring problems for the purpose of applying decision analysis. Belton emphasized a broad view by focusing on multi-criteria decision analysis (MCDA) and its integration with problem structuring methods and other OR approaches. The Belton-Stewart book Multiple Criteria Decision Analysis: An Integrated Approach published in 2002 emphasizes the integrative methodology.

Verbal Decision Analysis Oleg Larichev and Helen Moshkovich wrote an interesting book Verbal Decision Analysis for Unstructured Problems (1997), summarizing their research related to the topic. This book is devoted to a special class of decision problems called unstructured problems. Such problems are essentially qualitative. The book describes the decision-making environment and methods that improve the chances of making “sensible decisions in a complicated, contradictory and incompletely defined environment.” A new decision procedure for unstructured problems was constructed. The authors recognized the conflict between the normative methods of decision making and the descriptive models, demonstrating how decisions are made in real life.

Knowledge Discovery, Preference Modeling Knowledge discovery has penetrated the field of preference modeling, mainly due to the concept of dominance-based rough sets; an idea based on a suggestion by Stan Zionts at a conference (see Greco, Matarazzo, and

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Słowiński’s paper in Advances in Multiple Criteria Decision Making, 1999). The preference model is expressed as a set of “if-then” decision rules. An important feature of the dominance-based rough set approach is its capability to handle inconsistencies. Furthermore, the concept allows classification of decision rules into “certain” and “uncertain” rules. Besides theoretical research, the rough set community has also pursued many applications. The origins of the theory of rough sets go back to Zdzisław Pawlak’s paper “Rough Sets” in the International Journal of Computer and Information Science (1982), and Roman Slowinski’s book (1992).

Making Better Decisions in Practice John S. Hammond, Ralph Keeney, and Howard Raiffa wrote an awardwinning popular book, Smart Choices: A Practical Guide to Making Better Decisions, which was published by the Harvard Business School Press, 1999. The authors discuss what they call eight keys to effective decision making, including working on the right decision problem, specifying objectives, identifying creative alternatives, focusing on trade-offs, clarifying uncertainties, avoiding common decision traps, etc. Amazingly, this book has been translated into Arabic, Chinese, Danish, Dutch, Farsi, German, Italian, Japanese, Korean, Portuguese, Russian, Serbian, Slovenian, Spanish, Swedish, and Turkish. Hammond, Keeney, and Raiffa also published two influential Harvard Business Review articles in 1998: “The Hidden Traps in Decision Making” and “Even Swaps: A Rational Method for Making Trade-offs.” The former paper discusses and illustrates common decision traps faced by professional decision makers. Remedies are also offered to overcome these traps. “Even Swaps” is a simple decision tool, which decision makers can use to improve their decision making. It may be thought of as a formalization of a practical decision approach that the American statesman Benjamin Franklin used when making important choices, called a “Moral Algebra.” Thomas L. Saaty strongly advanced the practice of decision making via his analytic hierarchy process (AHP) during the 1990s. The AHP became the most widely used MCDM tool in practice. See, for example,

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the websites for Expert Choice3 and Decision Lens.4 His popular book on AHP in 1999, Decision Making for Leaders, has been translated into more than ten languages. Besides having regular workshops in western countries, Chinese AHP scholars have started having regular AHP workshops. Tom Saaty published his book Analytic Network Process: Decision Making with Dependence and Feedback in 1996. The analytic network process (ANP) is a more advanced framework for setting priorities in decision making. While AHP structures a decision problem into levels forming a hierarchy, ANP uses a network approach. According to Saaty, both approaches use pairwise comparisons to derive weights in the hierarchy and to rank the alternatives. However, in AHP, each element in the hierarchy is considered to be independent of all others; ANP does not require independence among elements. Interesting applications of ANP have appeared in decisions where risks and threats play a major role in the decision process.

Web-Based Decision Support Wallenius et al. (Man. Sci., 2008) wrote that In the early 1990s, we could foresee the continuing spread of personal computers and we could predict the popularity of spreadsheet modeling and spreadsheet solvers. We believe that we also anticipated the upcoming advances in computing power, but not necessarily all the consequences. However, we did not know about the popularity and the importance of the web protocol.

Tim Berners-Lee developed “hypertext” and the first web server for CERN at the end of the 1980s, and by 1991 the World Wide Web was born. The invention of the World Wide Web has created a need to support decision makers, even consumers, online. Today many MCDM tools can be operated via the World Wide Web. One of the first web-based MCDM decision support systems was 3 4

http://www.expertchoice.com, last accessed June 10, 2010. http://www.decisionlens.com, last accessed June 10, 2010.

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The Decisionarium software site (developed by the Aalto University School of Science and Technology Systems Analysis Laboratory) for interactive multicriteria decision support.

WWW-NIMBUS, an interactive multiobjective optimization system developed at the University of Jyväskylä by Kaisa Miettinen and Marko Mäkelä in 1995. Another early system was R. Hämäläinen and M. Pöyhönen’s online group decision support system for traffic planning published in Group Decision and Negotiation, in 1996. A more recent implementation on the web is the multiple criteria AIM procedure by Jingguo Wang and Stan Zionts (JMCDA, 2005).

Negotiation Analysis The literature on negotiation and group decision making is fascinating. Many MCDM scholars became interested in the group decision problem, some in the 80s, many in the 90s. Many of them followed in Howard Raiffa’s footsteps. See Raiffa’s classic book The Art and Science of Negotiation published by Harvard University Press in 1982.

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Prior to Raiffa’s book, Pekka Korhonen, Jyrki Wallenius, and Stanley Zionts published a paper addressing the bargaining problem in the Königswinter MCDM Conference Proceedings in 1980. They developed one of the first computer-based group decision support systems implemented on a time-sharing system. The negotiations begin with each group member determining his/her own most preferred solution. Then the model identifies the most discordant individual and tries to induce him/her to make concessions. Other active scholars in this area include Gregory Kersten and Wojtek Michalowski (formerly from Carleton University, Canada; Kersten is now at Concordia University and Michalowski is now at the University of Ottawa), Craig Kirkwood from Arizona State University, Ralph Keeney (now at Duke University), Harri Ehtamo, Raimo Hämäläinen and Hannele Wallenius from Aalto University School of Science and Technology (formerly Helsinki University of Technology), Jeffrey Teich from New Mexico State University, and Rudolf Vetschera, from the University of Vienna. The idea was to adopt what was useful in MCDM and apply it to the group decision problem. Despite the theoretical difficulties inherent in building a group value function, there was an established need to support practicing negotiators. NEGOPLAN was an early group decision support system by Kersten, Michalowski and colleagues. See their article about NEGOPLAN (Matwin et al., IEEE Intelligent Systems and Their Applications, 1989). See also the paper by Kersten et al. on the foundations of decision support in negotiations (Naval Research Logistics, 1991) and their paper in Management Science, 1991. Much research was devoted to supporting groups in finding “win-win” solutions. Examples of such software systems were Jeffrey Teich’s RAMONA for supporting two-party negotiations, originally published in his doctoral dissertation at SUNY Buffalo (1991), the directional search approach of J. Teich, H. and J. Wallenius, and S. Zionts (EJOR, 1996), and the joint gains approach by H. Ehtamo, E. Kettunen and R. Hämäläinen (EJOR, 2000). An interesting book is Melvin Shakun’s (the long-time editor of Group Decision and Negotiation) Negotiation Processes, published by Springer in 1996. This book focuses on how modeling frameworks and information technology can support negotiation processes. For a review paper on negotiation

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analysis, see Sebenius (1992). More recently, Wang and Zionts (EJOR, 2008) explore some considerations of multiple criteria decision making that lead to an approach to negotiation. Keeney, in a plenary talk at the ALIO-INFORMS Conference in Buenos Aires, June 2010, outlined some practical approaches to group decision making, based on using an additive group value function.

MCDM and DEA Valerie Belton in the IXth International MCDM Conference Proceedings in 1992 and R.H. Doyle and J.R. Green, in a 1993 article, described the relationships between MCDM and DEA. Subsequently, Tarja Joro, Pekka Korhonen and Jyrki Wallenius developed a detailed understanding of the structural (mathematical) relationship between DEA and multiple objective linear programming (MOLP) formulations in a paper published in Management Science in 1998. One of the fundamental differences is the radial projection used in DEA and the more general nonradial projection used in MOLP. In other words, DEA extends the ray from the origin via the point representing the decision making unit (DMU in DEA terminology) being evaluated to the efficient frontier when calculating efficiency scores; whereas MOLP techniques are more generic. Rhodes, Charnes, and Cooper’s DEA did not incorporate the preferences of the DM. They wanted it to be value-free. This was a problem, because a DMU could be efficient by being best in terms of one output measure, which might not be very important. One idea of incorporating preferences into DEA was to use weight restrictions. An early paper discussing weight restrictions was R.G. Dyson and E. Thanassoulis’ JORS paper, 1988. As shown by M. Halme, T. Joro, P. Korhonen, S. Salo5 and J. Wallenius in their Management Science (1999) paper, MOLP models can be used to find better ways to incorporate a DM’s preferences into DEA. Their procedure begins by the DM searching for her most preferred solution. Then, assuming that the DM’s most preferred solution 5

Seppo Salo was Professor of Mathematics at the Helsinki School of Economics for 25 years. He died at the age of 54 in 2001.

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Wallenius and Korhonen visiting University of Georgia, October 1994 (left to right: J. Wallenius, R. Davis, then president of the Decision Science Institute, P. Korhonen, R. Steuer).

maximizes her underlying (unknown) value function at the moment the search is terminated, the indifference contour of the value function is approximated at this point with its possible tangent hyperplanes. Value efficiency scores are then calculated for each DMU comparing the inefficient units to units having the same value as the most preferred solution, providing optimistic approximations of the true scores.

MCDM and e-Commerce During the latter part of the 90s MCDM began to play a role in many e-commerce applications. We mention two application areas for MCDM: multiattribute online auctions (in particular, reverse auctions) and shopping agents. Price-only auctions are too simple for many real-world purchasing situations. One cannot ignore other relevant attributes, such as quality, terms of delivery, terms of payment, etc., naturally leading to multiattribute

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auctions. How can we deal with the presence of multiple attributes in an auction setting? We must somehow capture the auction owner’s preferences over the relevant attributes. This task could be accomplished via eliciting a value function. This approach has been reportedly implemented by Martin Bichler and his colleagues, but we were unable to access the site. Alternatively, one could use ‘pricing out’ (or ‘costing out’) all other attributes besides price and quantity. For an auction implementation, see J. Teich, H. Wallenius, and J. Wallenius’ DSS paper on multiple issue auction and market algorithms for the World Wide Web from 1999. They also came up with the idea of providing price support to bidders. The purpose of the early shopping agents was to find the least expensive deals for buyers, focusing on the price of the merchandise. The assumption was that there would not be any quality differences among products/services. More advanced shopping agents, incorporating buyer’s preferences over multiple attributes were developed during the late 1990s. An example is the Tete-a-Tete shopping agent model described by Maes, Guttman, and Moukas in Communications of the ACM, 1999.

MCDM and Engineering In the 1990s MCDM began to penetrate many fields of engineering. Often, however, the application of MCDM methods to engineering problems was (and still is) based on the use of simple scoring models. Documented MCDM applications include, for example, aircraft design, chemical process optimization, environmental decision making, forest management, river basin development, water regulation, and radiation therapy. The Systems Analysis Laboratory web page at the Aalto University School of Science and Technology (formerly Helsinki University of Technology)6 provides information on several such MCDM applications. The book edited by Carlos Coello Coello and Gary Lamont provides a good coverage of EMO applications (2004). We also refer to Benjamin Hobbs and Peter Meier’s book from 2000 for a broad treatment of the use of MCDM methods in energy and environmental decision making. Also see Lahdelma, Salminen, and Hokkanen’s paper 6

http://www.sal.hut.fi/, last accessed June 10, 2010.

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in Environmental Management (2000). Their team pioneered several real-world applications. Complex applications of multiattribute utility theory to problems in the nuclear energy sector have been conducted. Von Winterfeldt and Schweitzer, in a paper published in Interfaces in 1998, evaluated alternatives for the replenishment of tritium in the US nuclear weapons stockpile. (This study influenced the US Secretary of Energy’s decision making process.) Other interesting applications from this era include Hora and von Winterfeldt’s paper dealing with nuclear waste, published in Technological Forecasting and Social Change in 1997 and Stewart and Scott’s paper on water resources planning, published in Water Resources Research in 1995. Also see Larichev and Olson’s book, Multiple Criteria Analysis in Strategic Siting Problems, by Kluwer, 2001. Multiple-response design problems consist of representing multiple performance characteristics (criteria) in terms of multiple design factors (decision variables). The aim is to choose the design factors that “optimize” the performance characteristics. Many early approaches during the 80s and 90s typically chose a composite objective to optimize (Eschenauer, Koski, and Osyczka, 1990). Köksalan and Plante, in their MSOM article in 2003, introduced the first interactive approach. The decision maker is involved to progressively provide preference information to obtain better design factors and to converge to preferred solutions. Later, other authors followed suit to develop preference-based approaches to multiple-response design problems.

Applications to Medicine G.W. Torrance, D.H. Feeny, and W. Furlong, with their research team, have actively published studies about medical decision making related problems. See, for example, three of their papers in Pharmaco Economics and Medical Care in the mid-90s, which were identified in our bibliometric study7 as highly cited (Torrance et al., Medical Care, 1996; Feeny et al., Pharmaco Economics, 1995; Torrance et al., Pharmaco Economics, 1995). The paper published in Medical Care discusses the Health Utilities 7

Bragge et al. (2009).

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Index, essentially a multiattribute utility function, for assessing healthrelated quality of life. The index consists of two components: a seven-attribute health status classification system and a scoring formula. Utilities were measured using a standard gamble technique. A scoring formula is provided, based on a multiplicative multiattribute utility function. The Pharmaco Economics papers deal with a related problem in multiattribute health status classification. Wojtek Michalowski is engaged in interesting medical decisionmaking research at the University of Ottawa. He is the Mobile Emergency Triage (MET) research program leader. MET is creating a methodological framework for “anytime and anywhere” decision support for Emergency Department triage decision making. “Triage” is defined as an Emergency Department activity that extends beyond the initial assessment and categorization. According to the project web site, the triage decision-making process involves gathering and evaluating information about a patient’s history, physical examination and additional tests, before deciding on a course of action. This may include further tests and/or several therapeutic options. Michalowski’s group has produced more than a dozen journal articles on supportive clinical decision making.

Multiobjective Combinatorial Optimization (MOCO) MOCO problems are typically computationally difficult, and one needs to resort to heuristics. The developments prior to 90s have been few. We mention the efficient procedure developed by Jared Cohon in his 1978 book, Aneja and Nair’s Management Science paper from 1979 to find all supported nondominated solutions of bi-criteria problems, as well as Climaco and Martin’s (EJOR, 1982) and Henig’s (EJOR, 1986) shortest path algorithms. Most MOCO problems addressed during the 1990s were bi-criteria problems. Bi-criteria versions of the knapsack, shortest path, spanning tree, assignment, and network flow problems were among the more commonly studied problems. Ulungu and Teghem (JMCDA, 1994) present a survey of the research in MOCO. Multiobjective scheduling problems deserve special attention as they have been addressed by many researchers. An early approach to

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bi-criteria scheduling was developed by Van Wassenhove and Gelders (EJOR, 1980). Many authors addressed bi-criteria problems with total flowtime (total time spent in the system by all jobs) and some form of earliness or tardiness criteria (see, for example, Hogoveen’s Ph.D. thesis, 1992 and Köksalan, Azizoglu, and Kondakci, IIE Transactions, 1998). Köksalan (Naval Research Logistics, 1999) developed an approach to approximate the nondominated set for bi-criteria scheduling problems which was later generalized for more than two criteria cases as well as other MOCO problems. Metaheuristics were also employed for multicriteria scheduling problems (see, for example, Ishibuchi and Murata, IEEE Transactions on SMC, 1998, for an implementation of genetic algorithms).

Theory and Approximations in the Criteria Space Harold Benson made important contributions to the theory of MCDM during the 90s, particularly in optimizing over the efficient set, as well as generating the efficient and nondominated solutions in the decision and criterion spaces, respectively (see, for example, Benson and Sayin, Naval Research Logistics, 1993; Benson, J. of Global Optimization, 1995; JOTA, 1998; Benson and Sun, EJOR, 2002). Jerald Dauer has contributed to these areas as well (see, for example, Dauer, ZOR, 1991; Dauer and Gallagher, EJOR, 1996). As opposed to characterizing the complete set of efficient solutions or nondominated solutions, some researchers worked on the more practical problem of finding a representative set of solutions, thereby approximating the nondominated frontier. Examples of such approaches can be found in the work of Sayin (Opns. Res., 2003), Karasakal and Köksalan (Opns. Res., 2009) and Köksalan and Lokman (NRL, 2009). Ruzika and Wiecek (JOTA, 2005) present a survey of such approximation methods.

Multiple Criteria Sorting Multiple criteria sorting and classification problems became popular during the 1990s. Sorting refers to the classification of alternatives into preference-ordered categories where each alternative is defined by a

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set of criteria. Categorizing countries into different risk groups based on their reliability to repay debt, and star-based categories of hotels and restaurants are typical examples of the sorting problem. W. Yu and Bernard Roy developed the outranking-based approach, ELECTRETRI, in 1992 (see, for example, Mousseau and Słowiński, J. Global Opt., 1998) and Larichev and Moshkovich (Int. Trans. Oper. Res., 1994) developed a sorting approach for ordinal criteria based on dominance. Eric Jacquet-Lagreze, in a book chapter (1995), developed the UTADIS method based on additive utility functions. Other utility-based approaches for the sorting problem were developed by Köksalan and Ulu (EJOR, 2003), and Köksalan and Özpeynirci (Comp. OR, 2009). Greco, Matarazzo, and Słowiński’s (EJOR, 2002) rule-based approach is an example of approaches developed for the sorting problem that utilize “rough sets” methodology. Bouyssou and Marchant (EJOR, 2007) provide an axiomatic analysis for the noncompensatory sorting methods. Bouyssou and Pirlot (EJOR, 2009) present an axiomatic analysis of concordance and discordance relations, that applies to methods based on outranking relations in general. For a survey of sorting problems and their applications, the reader is referred to Zopounidis and Doumpos (EJOR, 2002).

More Recent MCDM Developments and Trends One of the major events in the field in the past decade was the recognition of its importance when Daniel Kahneman was awarded the Nobel Prize in Economics in 2002. Daniel Kahneman, together with the late Amos Tversky, has made important contributions to the behavioral aspects of decisions. At the 15th International Conference on MCDM in Ankara, Turkey, the theme was “Challenges for MCDM in the New Millenium.” In line with the theme, a panel discussion took place, chaired by Pekka Korhonen. Panelists were Valerie Belton, Murat Köksalan, the late Oleg Larichev, Theo Stewart, Jyrki Wallenius, and Stan Zionts. Two promising areas cited at the time were multiobjective combinatorial optimization (MOCO) and heuristic approaches. Both these topics attracted many researchers indeed and numerous publications have

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appeared in the literature since then. Among the heuristic approaches, the growth of evolutionary multiobjective optimization (EMO) has been phenomenal. We mentioned a MOCO review article published in the 1990s. More surveys appeared after the year 2000. Ehrgott and Gandibleux surveyed MOCO research in a book chapter in 2002, and T’Kindt and Billaut (RAIRO, 2001) reviewed the related literature on multi-criteria scheduling. Research continued on MOCO that included such topics as shortest path, spanning tree, assignment, knapsack, location, and traveling salesperson problems, all with a multiobjective perspective. Bi-criteria versions of these problems have been widely addressed and many approaches have tried to generate all nondominated solutions (see, for example, Raith and Ehrgott, Comp. OR, 2009). Nickel, Puerto, and Rodriguez-Chia (2005) review multiobjective location problems in a book chapter. The hub location problem has been studied in depth as a single objective problem in recent years. The hub location problem is important for airlines, shipping companies, telecommunication companies and computer network companies. More recently, bi-criteria versions of this problem have been considered and this area may attract more researchers in the near future (see, for example, Costa, Captivo, and Climaco, Comp. OR, 2008, and Köksalan and Soylu, INFORMS JOC, 2010). There is software available for the single objective traveling salesperson problems that can solve fairly large problems.8 Of course this software may be used with a weighted sum of objectives to find supported efficient solutions. Finding unsupported efficient solutions for the general case is difficult. Feillet, Dejax, and Gendreau (Transp. Sci., 2005) discuss certain two-objective cases. Özpeynirci and Köksalan (EJOR, 2009) consider some special cases of the multiobjective traveling salesperson problem and categorize them as polynomially solvable and NP-Hard. In EMO, much of the research prior to 2000 had been to approximate the entire Pareto-optimal frontier. Work has continued along these lines in recent years. Many successful algorithms have been developed; see, for 8

www.tsp.gatech.edu/concorde, last accessed May 16, 2010.

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example, NSGA-II (Deb et al., IEEE Trans. on EC, 2002), SPEA2 (Zitzler, Laumanns, and Thiele, EUROGEN, 2002), ε-MOEA (Deb, Mohan, and Mishra, Evol. Comp., 2005), and FWEA (Soylu and Köksalan, IEEE Trans. on EC, 2010). Generating the Pareto-optimal frontier is difficult and impractical for problems having a large number of objectives. Coello (2000) reviews the literature that incorporates preference information prior to 2000. There are some approaches that incorporate preference information to guide the EMO algorithm towards preferred regions (see, for example, Deb and Sundar, GECCO, 2006, and Karahan and Köksalan, IEEE Trans. on EC, 2010). The literature on preferencebased approaches in MCDM in general and the literature on interactive preference-based approaches is both rich and extensive. As discussed earlier many important approaches were developed during the 1970s and 1980s. This rich literature has been recently discovered by EMO researchers. The first interactive EMO approach was developed by Phelps and Köksalan (Man. Sci., 2003), to the best of our knowledge. Several other interactive approaches have been developed since then (see, for example, Branke et al., EMO, 2009; Deb and Kumar, GECCO, 2007;

Boat seminar, Tallinn old town square, May 2008 (left to right: K. Deb, J. Wallenius, P. Korhonen, M. Köksalan).

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Thiele et al., Evol. Comp., 2009, and Köksalan and Karahan, IEEE Trans. on EC, 2010). Kalyanmoy Deb and Murat Köksalan edited a special issue on “Preference-based Multiobjective Evolutionary Algorithms” IEEE Transactions on Evolutionary Computation, Vol. 14, No. 5, October 2010. We will most likely see more preference-based EMO approaches and more collaboration between the EMO community and the MCDM community in the future. The books by Deb (Multi-Objective Optimization Using Evolutionary Algorithms, 2001) and Coello, Lamont, and Veldhuizen (Evolutionary Algorithms for Solving Multi-Objective Problems, 2006) cover some of the developments in EMO (see also Sequential Approximate Multiobjective Optimization Using Computational Intelligence, by Nakayama, Yun, and Yoon, 2009). Carlos Coello Coello maintains a repository of publications in EMO.9 The repository statistics demonstrate the rapid growth of this field. The yearly number of publications included in the repository grew from 24 in 1994 to 204 in 2000, and to 598 in 2009. Over 500 publications have been listed for each year from 2007 to 2009. The majority of publications are conference papers, followed by journal articles. Although the repository does not cover all EMO publications, it gives an indication of the speed and nature of the growth of the field. The need for employing multiple objectives in financial decisionmaking problems has been increasingly recognized in recent years. In classical portfolio optimization, the expected return and the variance have long been considered the two conflicting criteria. More recently, measures other than variance have been considered for measuring the risks associated with portfolios (see, for example, Steuer, Qi, and Hirschberger, Annals of OR, 2007). Balibek and Köksalan (EJOR, 2010) formulated the public debt management problem as a multiple criteria problem and treated risk using several proxy criteria. Yong Shi and his colleagues (Shi et al., Int. J. ITDM, 2005 and Peng et al., DSS, 2008) developed credit evaluation procedures for large data sets based on multiple criteria. Gwo-Hsiung Tzeng and his colleagues (Lee et al., Exp.

9

http://www.lania.mx/~ccoello/EMOO/, last accessed May 17, 2010.

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Sys. With App., 2009) explore the stock selection problem and Wu, Tzeng, and Chen (Exp. Sys. With App., 2009) evaluate banking performance based on multiple criteria. Further developments on the use of multiple criteria in financial decision making can be found in Hallerbach and Spronk (JMCDA, 2002), Steuer and Na (EJOR, 2003), and Spronk, Steuer, and Zopounidis (2005). Wallenius et al. (2008) explore recent accomplishments in the field, and speculate on the future of MCDM.

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The seeds of the first International MCDM Conference were planted in a conference held at the University of South Carolina, October 26–27, 1972. Milan Zeleny, then a Ph.D. student at the University of Rochester, organized and chaired the conference. According to him, about 250 people participated, presenting a total of 63 papers. Among the participants were C. West Churchman, Robyn Dawes, James Dyer, Peter Fishburn, Paul Green, James Ignizio, Yuji Ijiri, Heinz Isermann, Ralph Keeney, Kenneth MacCrimmon, Ury Passy, Bernard Roy, Ralph Steuer, P.L. Yu, and Lotfi Zadeh. The following year, the University of South Carolina Press published the conference proceedings, titled “Multiple Criteria Decision Making,” edited by James L. Cochrane and Milan Zeleny. Some of the topics covered at the conference included multiattribute utility, multidimensional scaling, outranking relations, domination structures, compromise programming, efficient extreme points, group decision making, as well as some environmental and medical applications. These were most current topics!

Official Conferences of the International Society on MCDM The 1st official International MCDM Conference was organized by Stanley Zionts and Hervé Thiriez in Jouy-en-Josas, near Paris, France, May 21–23, 1975. There were 78 participants from 15 different countries. The purpose was to discuss the current state of the art with respect to both theory and practice. The conference proceedings1 included papers by 1

Thiriez, H. and Zionts, S. (Eds.) (1976). “Multiple Criteria Decision Making,” Proceedings, May 1975, Jouy-en-Josas, France, Number 130. Lecture Notes in Economics and Mathematical Systems: Operations Research, Springer-Verlag, Berlin. 63

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(Left) Cover of the Proceedings (published in 1973) of the South Carolina MCDM Conference (1972) edited by J. Cochrane and M. Zeleny. (Right) The proceedings of the first official conference (Jouy-en-Josas 1975) of the Special Interest Group on MCDM. The 21st conference will be held in Jyväskylä, Finland in 2011.

Günter Fandel and Jochen Wilhelm (“Rational Solution Principles and Information Requirements as Elements of a Theory of Multiple Criteria Decision Making”), Pierre Hansen et al. (“Quasi-Kernels of Outranking Relations”), Ralph Keeney (“Quantifying Corporate Preferences for Policy Analysis”), Bernard Roy (“From Optimization to Multi-Criteria Decision Aid”), Ralph Steuer (“A Five-Phased Procedure for Implementing a Vector–Maximum Algorithm for Multiple Objective Linear Programming Problems”), Philip Vincke (“A New Approach to Multiple Criteria Decision Making”), and Jyrki Wallenius and Stanley Zionts (“Some Tests of an Interactive Programming Method for Multicriterion Optimization and an Attempt at Implementation”). The Jouy-en-Josas Conference started a tradition of roughly biennial MCDM conferences, often accompanied by Springer-Verlag Proceedings, that has continued until today. The field was small; everybody knew everybody in

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the field. The seeds of international cooperation and friendship among the MCDM scholars were planted. The 2nd MCDM Conference was organized by Stanley Zionts at the State University of New York in Buffalo, New York, August 22–26, 1977, with the help of an informal coordinating committee consisting of James Dyer, Peter Fishburn, Ralph Keeney, Bernard Roy, and Milan Zeleny. The conference was small (40 participants), but of very high quality. The small size made intense interactions among the participants possible. No parallel sessions were needed! Some of the participants, in addition to the coordinating group members, were David Bell, Samuel Bodily, Hillel Einhorn, Peter Farquhar, Tomas Gal, Yacov Haimes, Craig Kirkwood, Sang Lee, Rakesh Sarin, Ralph Steuer, Jyrki Wallenius, and Donald Wehrung. Some practitioners were also invited to attend, including Don Keefer from Gulf Oil Corporation. The Buffalo Conference started the tradition of a conference outing. It was fitting that the outing destination was Niagara Falls. Other highlights of the conference included fine wines served with meals. The 3rd MCDM Conference was organized by Günter Fandel and Tomas Gal in Hagen/Königswinter, Germany, August 20–24, 1979, with the assistance of Bertil Tell and Jyrki Wallenius as members of the organizing committee. Following the Buffalo conference tradition, the Königswinter Conference was small, with 37 papers presented. Theoryand method-focused presentations dominated, which was typical of the

Königswinter conference chairs, August 1979 (left: Günter Fandel, right: Tomas Gal).

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times. A highlight of the conference proceedings included a paper by Wierzbicki (1980), “The Use of Reference Objectives in Multiobjective Optimization.” The participants included as newcomers, Gabriel Bitran, Joe Ecker, Johannes Jahn, Hirotaka Nakayama, Vladimir Ozernoy, Jaap Spronk, and Andrzej Wierzbicki. The outing was a boat cruise on the Rhine River. At this conference we formalized the society, calling it the Special Interest Group on Multiple Criteria Decision Making. The 4th MCDM Conference was organized by Joel Morse at the University of Delaware, Newark, August 10–15, 1980. This conference saw the birth of the worldwide MCDM Executive Committee. This conference was also small, with roughly 50 participants. We welcomed newcomers, including Jared Cohon, Lori Franz, Mordecai Henig, Pekka Korhonen, and Wojtek Michalowski. Joel Morse recalls an animated discussion between David Bell and Paul Schoemaker, causing Mathilde Stephenson to stand up and say, “Don’t stop it; this is the best part of the conference!” The conference outing included a trip to a mushroom farm and the Winterthur Estate. The 5th MCDM Conference was organized by Pierre Hansen at FUCAM in Mons, Belgium, August 9–13, 1982. The number of participants had begun to grow, totaling about 70 people who presented 50 papers. Newcomers included Valerie Belton, Lucien Duckstein, Manfred Grauer, Marc Roubens, Tom Saaty, and Martin Weber. The Vice-Dean of FUCAM, Alain Bultez, a former faculty member of the European Institute for Advance Studies in Management (Brussels), took a keen interest in the conference. One of the objectives of the conference was the establishment of closer contacts with the European Working Group on Multiple Criteria Decision Aid, chaired by Bernard Roy from LAMSADE, in France. Another objective was the encouragement of real-world application papers, as well as interdisciplinary research. According to Pierre Hansen, the pleasant and stimulating atmosphere was not hindered by the weather, which was bad during sessions and sunny during social events! The 6th MCDM Conference was organized by Yacov Haimes at Case Western Reserve University, Cleveland, Ohio, June 4–8, 1984. The conference was attended by about 100 participants from 15 different countries. There were four plenary sessions and three panel discussions. The plenary speakers were Vira Chankong, Yacov Haimes, Tom Saaty, P.L. Yu, and Stanley Zionts. Decision support systems and interactive

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procedures were some of the main topics discussed at the conference. The outing was a boat trip on Lake Erie and the Cuyahoga River. The 7th MCDM Conference was organized by Hirotaka Nakayama and Yoshikazu Sawaragi in Kyoto, Japan, August 18–22, 1986. The conference theme was “Toward Interactive & Intelligent Decision Support Systems.” The total number of participants exceeded 120, and included the Russian scholar Boris Berezovsky (now a billionaire fugitive) from the USSR Academy of Sciences, who gave a talk entitled, “Symmetries in Multicriterial Optimization and Their Application.” More than half of the delegates were from Japan. Moreover, over 50 Japanese corporations provided funding for the conference. The 8th MCDM Conference was organized by Geoff Lockett and Gerd Islei at the Business School of the University of Manchester, UK, August 21–26, 1988. The theme of the conference was “Improving Decision Making in Organizations.” There were 101 participants from 27 countries and 91 papers were presented. Also, numerous software packages were demonstrated. Dormitory accommodation on campus notwithstanding, the social program included a theatre visit and an excursion to the Lake District. During the banquet the fastest “Pareto Race drivers,” Murat

From left: Hirotaka Nakayama, Yoshikazu Sawaragi, Jaap Spronk, Andrzej Wierzbicki, Geoff Lockett, Stan Zionts, and Pekka Korhonen at the Manchester (UK) conference in 1988.

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Pareto Race contest winners Vahid Lotfi (left) and Murat Köksalan (right) getting their awards from the developers Pekka Korhonen (center left) and Jyrki Wallenius (center right), Manchester 1988.

Köksalan and Vahid Lotfi, received free software of VIG (implementing Pareto Race), a software system developed by Korhonen in 1987. The 9th MCDM Conference was organized by Ambrose Goicoechea and Richard Soland at George Mason University, Fairfax, USA, near Washington D.C., August 5–8, 1990. The theme of the conference was “At the Interface of the Needs in Industry, Business and Government.” For three days before the conference, there was a pre-conference for the 25 participants from the Soviet Union. There were 143 participants from 26 countries. The conference banquet was held at George Washington University in downtown Washington. In addition to outings to Washington, D.C., the participants were treated to a professional Baltimore Orioles’ baseball game, organized by Jared Cohon. Participants stayed in the dormitories at George Mason University. The 10th MCDM Conference was organized by G.H. Tzeng and P.L. Yu, in Taipei, Taiwan, at the Asiaworld Plaza Hotel, July 19–24, 1992. The theme of the conference was “Expand and Enrich the Domains of Thinking and Applications.” It was highly publicized in Taiwan. The

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Registration at the Taiwan conference, Taipei, 1992 (some participants identified from left: Murat Köksalan, x, x, Milan Zeleny, Ralph Steuer, Peri Iz, Yasemin Aksoy, Pekka Korhonen, Judy Steuer, x, x).

Stan Zionts presenting his paper at the Taiwan conference, 1992.

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The first MCDM Gold Medal, presented to Stanley Zionts, Taipei July 1992.

conference was attended by more than 300 people from 34 countries. The organizers raised a large amount of money from sponsors and were able to host one of the grandest conferences, with a wonderful social program. The awards tradition was started at this conference. The Gold Medal was awarded to Stanley Zionts, the Edgeworth-Pareto Award jointly to Po-Lung Yu and Milan Zeleny, and the Georg Cantor Award was awarded to Andrzej Wierzbicki, all pioneers of MCDM. At this meeting, the awardees did not deliver award lectures. The 11th MCDM Conference was organized by Joao Climaco, at one of the oldest European universities, University of Coimbra, Portugal, August 1–6, 1994. The theme of the conference was “Helping to Make the World a Better Place.” The conference was attended by 142 participants from 35 countries. In addition to the usual theory and decision support

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papers, behavioral issues were receiving increased attention. Academician Oleg Larichev, who was one of the leading figures in Russia in the psychology of decision making, received the Gold Medal of the Society. In addition, the other two award winners, Pekka Korhonen and Jyrki Wallenius, chaired a Saturday session on behavioral issues in MCDM. An outing was organized to Bucaco forest and to the town of Porto, the heart of port wine production. Additional highlights included the banquet at the San Marcos palace and a tour of an incredible library, the baroque Biblioteca Joanina, built around 1720. The 12th MCDM Conference was organized by Günter Fandel and Thomas Gal at Fernuniversität, the largest correspondence university in Germany, June 18–23, 1995. Günter Fandel was serving as Rector of the University at the time. The theme of the conference was “Twenty Years of East-West Cooperation and Friendship in MCDM.” 152 participants from 34 countries attended the conference. One of the major objectives was to facilitate the attendance of researchers from Eastern Europe and Third World countries. The social program included an outing to the Westphalia Open-Air Museum. The 13th MCDM Conference was organized by Theo Stewart at the University of Cape Town, South Africa, January 6–10, 1997. This was the first MCDM conference in the southern hemisphere. The conference was attended by 143 delegates from 35 countries. The 123 papers presented covered both theory and applications of MCDM. The two plenary lectures were delivered by P.L. Yu (based on a joint paper with Herbert Moskowitz) and Stanley Zionts. At the conference banquet Stanley Zionts, the founding President of our Society, was presented with a Festschrift “Essays in Decision Making” (edited by Mark Karwan, Jaap Spronk and Jyrki Wallenius) by Jyrki Wallenius and Jaap Spronk to celebrate his imminent 60th birthday. The outing included an excursion through the wine country (Stellenbosch and KWV cellars in Paarl), as well as a visit to the Table Mountain. Many participants also visited the Cape of Good Hope, where the currents of the Atlantic and Pacific Oceans meet, on their own. The 14th MCDM Conference was organized by Yacov Haimes at the University of Virginia, Charlottesville, Virginia, June 8–12, 1998. The theme of the conference was “MCDM and its Worldwide Role in

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Top: Jyrki Wallenius (left) and Jaap Spronk (center) presenting Stan Zionts (right) an Honorary Volume (Cape Town 1997) on the occasion of his 60th birthday. Bottom: Stan just before receiving the honorary volume (left), the cover of the volume (right).

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14th International Conference, Charlottesville, Virginia, June 1998 (left to right: Esra Karasakal, Hannele Wallenius, Johanna Wallenius, Suna Kondakcıı Köksalan, Barıış Köksalan, Serpil Sayıın, Murat Köksalan, Jyrki Wallenius, Meral Azizoğğlu, GwoHsiung Tzeng).

From left: Ron Klimberg, Maureen and Jared Cohon, and Ralph Steuer at the Charlottesville conference, June 1998.

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Risk-Based Decision Making.” Topics covered at the conference included theory and methodology, applications of MCDM in the private and public sectors, risk management within the MCDM framework, mathematical and algorithmic developments in MCDM, social and behavioral studies of MCDM processes, conflict resolution, negotiation and group decision support, and MCDM software. In total, 159 papers were presented at the conference, including the “Even Swaps Method” by Ralph Keeney and Howard Raiffa, as well as Carnegie-Mellon University’s President, Jared Cohon’s “Sustainable Development as a Decision Making Problem.” The International Society on Multiple Criteria Decision Making was officially formed at this conference. The outing included a visit to Monticello, Thomas Jefferson’s home. Accommodation was provided on campus at the University of Virginia. The 15th MCDM Conference was organized by Murat Köksalan on the campus of the Middle East Technical University in Ankara, Turkey, July 10–14, 2000. The year 2000 offered a timely opportunity for taking stock of past developments in the field, as well as looking ahead at the

Panel — Challenges for MCDM in the New Millennium — Ankara Conference 2000. Left to right: Korhonen, Zionts, Wallenius, Stewart, Larichev, Köksalan, Belton.

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ANKARA 2000 Participants of Ankara (2000) conference.

trends and future requirements. The conference theme was appropriately “Challenges for MCDM in the New Millennium.” In total, 194 people from 36 countries participated. The Turkish participation was strong. The plenary talk was given by P. L. Yu. Other conference highlights included a panel about the future of our field, chaired by Pekka Korhonen, as well as tutorials delivered by Ralph Steuer about multiobjective optimization and Pekka Korhonen about value efficiency in data envelopment analysis. At the conference banquet Yong Shi and Milan Zeleny presented a Festschrift “New Frontiers of Decision Making for the Information Technology Era” to honor P.L. Yu’s contributions to MCDM. The conference banquet took place outdoors at the Ankara Palace. The outing included a city tour of the old part of the city. The 16th MCDM Conference was organized as a winter conference in the Austrian Alps at Semmering, by Mikulas Luptacik and Rudolf Vetschera, in February 2002. This conference was small, comprising 99 delegates from 31 countries. The idea was that participants could ski during the day, preceded by morning sessions and followed by evening

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sessions. Though the town and accommodations were magnificent, and the weather was beautiful and warm, the conditions were not really good for skiing. Many dauntless participants did ski nonetheless. The 17th MCDM Conference was organized by William Wedley at the Whistler Conference Centre at the Whistler Mountain Ski Resort (the site of the 2010 Winter Olympics), British Columbia, Canada, August 6–11, 2004. The participation rate had stabilized in the range of 150 to 200 participants, necessitating some parallel sessions. Highlights of the conference included a plenary by Kalyanmoy Deb from the Indian Institute of Technology (Kanpur) about evolutionary multiobjective optimization, a topic of increasing importance; and a panel about new challenges chaired by Raimo Hämäläinen, the recipient of the EdgeworthPareto award at the Whistler Conference. Furthermore, applications to

Awardees at the Whistler conference, held at Whistler, British Columbia, Canada, August 2004 (from left: Bill Wedley, Conference Chair Award; Harold Benson, Georg Cantor Award; Valerie Belton, Past President Award; Raimo Hämäläinen, Edgeworth-Pareto Award).

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C. Zopounidis (center) receiving Conference Chair Award, Chania 2006, Theo Stewart (left) and Murat Köksalan presenting the award.

finance were gaining importance. The outing was a gondola ride up the mountain and a hike in the mountains. Many of us saw bears from a ski lift! The 18th MCDM Conference was organized by Constantin Zopounidis in Chania, Greece, June 19–23, 2006. At the conference, 215 papers were presented, covering many recent trends and advances in MCDM/MCDA and their real-world applications. Theo Stewart, the President of the Society at the time, expressed it well, “But a conference is much more than just a collection of papers! The formal papers do form the seeds from which grow deep discussions and new ideas. […]The real value of a conference such as this, however, is in the networking which it creates.” Roman Słowiński delivered the plenary, comparing utility functions and decision rules. Increased attention was devoted to multiobjective combinatorial optimization problems. Moreover, the first presentations dealing with the interface between MCDM and evolutionary multiobjective optimization emerged. During the conference several of us stayed in the former British Embassy, which now serves as a hotel. The outing included some outdoor activities, helping us to discover the beauty and the rich history of Chania.

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The 19th MCDM Conference was organized by Matthias Ehrgott at the University of Auckland, New Zealand, January 7–12, 2008. Some 160 delegates participated in the conference. The theme was “MCDM for Sustainable Energy and Transportation Systems,” reflected in the many

G.-H. Tzeng improvising a long talk when several speakers did not show up, Auckland conference, January 2008.

Matthias Ehrgott (center) receiving Conference Chair Award, Auckland, January 2008.

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Before the banquet on Waiheke Island, Auckland, New Zealand, January 2008.

presentations about applications to natural resources. Anna Nagurney and Jim Petrie delivered the plenary talks. Evolutionary multiobjective optimization was allocated a track of its own. The conference banquet took place on the beautiful Waiheke Island, in the midst of several vineyards. The social program included a Powhiri, a Maori welcoming ceremony, and a visit to the Auckland Museum. The 20th MCDM Conference was organized by Yong Shi and Shouyang Wang, at the campus of the University of Electronic Science and Technology, China (UESTC), in Chengdu, Sichuan Province, China, June 21–26, 2009. The conference was preceded by an intense day of tutorials and workshops delivered mainly to a large Chinese audience, demonstrating a keen interest in Management Science and MCDM in China. Some 100 people participated in the actual conference. Five “old timers” delivered keynote speeches, with historical focuses, namely James Dyer, Yacov Haimes, Po-Lung Yu, Milan Zeleny, and Stanley Zionts. There was a choice of outing to Mount Emei or to Jiuzhaigou (Valley of Nine Villages), both spectacular nature reserves in the mountains of Sichuan Province.

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Chengdu, China, June 2009.

Outing to Jiuzhaigou after the Chengdu, China conference, June 2009 (from left: PoLung Yu, Murat Köksalan, Yong Shi, Stan Zionts, Terri Zionts).

Mount Emei could be reached by bus, but Jiuzhaigou was an hour’s flight from Chengdu. The conference and outing was, for many Westerners, a most memorable, and in some instances, a first visit to China.

IIASA Workshops The International Institute for Applied Systems Analysis (IIASA) in Laxenburg, Austria, has played an important role in our field. Two of IIASA’s

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Directors have been awarded the Society’s Gold Medals, the first Director Howard Raiffa (1972–1975) in 1998 and the current Director, Detlof von Winterfeldt (at IIASA 1975–1978 and again) in 2009. In addition to Howard Raiffa and Detlof von Winterfeldt, many prominent MCDM scholars have worked at IIASA. These include Ralph Keeney (1974–1976), David Bell (1973–1975), Andrzej Wierzbicki (during the 1980s), A. Kurzhanski (during the 1980s), Wojtek Michalowski (1997–1998), Gregory Kersten (1997– 1998), Pekka Korhonen (1997–1998), Manfred Grauer (during the 1980s), Andrzej Lewandowski (during the 1980s), and Freerk Lootsma (1999). A number of these researchers have served IIASA in a leadership capacity. In addition, the popular Young Scientists Summer Program (YSSP) has hosted many neophyte MCDM scholars. The first MCDM workshop organized by IIASA took place in October 20–24, 1975. The papers presented at this workshop were published by Wiley as a book, Conflicting Objectives in Decisions in 1977 and edited by David Bell, Ralph Keeney and Howard Raiffa. Participants and contributors included, in addition to the editors, James Dyer, Ward Edwards, Peter Fishburn, A. Kurzhanski, Duncan Luce, Hirotaka Nakayama, Bernard Roy, Y. Sawaragi, Amos Tversky, and Stanley Zionts. In total, the book included 18 presentations. The 1975 workshop was followed by a sequence of MCDM workshops (under different titles) organized under the leadership of Andrzej Wierzbicki either at IIASA or at an IIASA member country during the 1980s. To facilitate the participation of Eastern European and Soviet scientists, many of the conferences were held in Eastern European countries. The first of them (Multiobjective and Stochastic Optimization) took place at IIASA on November 30–December 4, 1981. The proceedings were edited by Manfred Grauer, Andrzej Lewandowski and Andrzej Wierzbicki, who all played an important role in MCDM at IIASA. Many of the papers were by Eastern European, Japanese, German, Finnish and US scholars, reflecting the IIASA membership. This diversity was maintained at other IIASA workshops. The second workshop (Interactive Decision Analysis and Interpretative Computer Intelligence) was held at IIASA, September 20–23, 1983. In 1989 the IIASA workshop (Multiple Criteria Decision Support) was organized in Espoo, Finland by Pekka Korhonen and Jyrki Wallenius. Pekka Korhonen served as the project leader of the Decision Analysis and Support (DAS) Project at IIASA from 1997–1998, with

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participation from Gregory Kersten, Wojtek Michalowski, Kaisa Miettinen, Margareta Soismaa, and Jyrki Wallenius, followed by Freerk Lootsma in 1999 as the new project leader. The team organized several workshops, including one held in Büyükada, one of the Princess

IIASA DAS Workshop, September 1998, Büyükada, Istanbul (from left, sitting: Johanna Wallenius, Hannele Wallenius, Barıış Köksalan, Jyrki Wallenius; standing: Tom Morin, Suna Kondakcıı Köksalan, Murat Köksalan, Jeffrey Teich).

Oleg Larichev (left) and Alexander Lotov (right) on the Bosphorus, during the IIASA DAS Workshop, September 1998.

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Islands, in Istanbul, Turkey in September 1998. The project was phased out at the end of 1999. Since 2000 IIASA has no longer had a methodology project of its own. MCDM work has been carried out in applied projects. One of the key persons has been and still is Marek Makowski.

Other Workshops and Conferences The European Working Group (EWG) on Multiple Criteria Decision Aid (MCDA) was established by Bernard Roy at the EURO I Conference in Brussels in 1975. The EWG on MCDA has been most successful. It now has about 300 members. It has held semi-annual workshops in different European countries beginning in 1975. In earlier years most of the

EWG Meeting, Prague, former Czechoslovakia 1991. From Left: Constantin Zopounidis, Jean-Claude Vansnick, Mrs. Vansnick, Françoise Roy, Bernard Roy, Carlos Bana e Costa, Walter Habenicht, Roman Słłowińński, Pierre Hansen, Yannis Siskos.

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presentations were in French. However, an increasing number of English presentations have taken place in recent years. Roughly 30 presentations are made at each workshop. The focus has been on the French school of thought. The 72nd Meeting of the EWG on MCDA was held in Paris, France, October 7–9, 2010. Birsen Karpak and Stan Zionts organized a NATO Advanced Study Institute, “Multiple Criteria Decision Making and Risk Analysis Using Microcomputers,” at Tarabya, Istanbul, Turkey by the beautiful Bosphorus from June 28–July 8, 1987. Jean Pierre Brans, Murat Köksalan, Jaap Spronk, Ralph Steuer, the late Amos Tversky, Jyrki Wallenius, and Stan Zionts were among the speakers. The First International Conference on Evolutionary Multi-Criterion Optimization (EMO) took place in Zurich, Switzerland, March 7–9, 2001, with Kalyanmoy Deb, Lothar Thiele, and Eckart Zitzler as general chairs. In total, 45 papers were presented at the conference. The proceedings were published in the LNCS series by Springer-Verlag, with Eckart Zitzler, Kalyanmoy Deb, Lothar Thiele, Carlos A. Coello Coello, and David Corne as editors. The EMO Conferences have been organized every other year since then. The Second EMO Conference was organized in Faro, Portugal, April 2003. The Third EMO Conference was organized in Guanajuato, Mexico, March 2005, the Fourth EMO Conference was organized in Tohoku University, Matsushima-Sendai, Japan, March 2007. The most recent (Fifth) EMO Conference took place in Nantes, France, April 7–10, 2009, with Carlos Fonseca and Xavier Gandibleux as general chairs. The fifth conference had an MCDM track, to foster collaboration with the mainstream MCDM community. The EMO Conferences have always produced a proceedings volume. The number of presentations has steadily grown from 45 to over 60. To build bridges between the MCDM and EMO communities, which developed separately until 2004, a series of Dagstuhl Seminars were organized in Schloss Dagstuhl, Leibniz Center for Informatics, in Germany. The First Dagstuhl Seminar on “Practical Approaches to Multi-Objective Optimization” was organized in November 2004.2 The 2

http://www.dagstuhl.de/en/program/calendar/semhp/?semnr=04461 (seminar); http://drops. dagstuhl.de/portals/index.php?semnr=04461 (proceedings), accessed June 6, 2010.

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organizers were Juergen Branke (University of Karlsruhe, Germany), Kalyanmoy Deb (IIT Kanpur, India), Kaisa Miettinen (then Helsinki School of Economics, Finland) and Ralph E. Steuer (University of Georgia, USA). According to the seminar organizers, during the First Dagstuhl Seminar, two conclusions clearly emerged: first, getting both MCDM and EMO researchers and practitioners together in one seminar for five days was beneficial to both groups in terms of enhancing our understanding of each other’s approaches and fostering collaboration; and second, it was felt that there was a need to follow up on the MCDM/EMO joint Dagstuhl seminars. Accordingly, the Second Dagstuhl Seminar was organized in December 2006 and the Third in January 2009. The team of organizers has remained the same, with the exception of Roman Słowiński replacing Ralph Steuer. About 50 to 60 researchers have attended the seminars, roughly half were MCDM scholars, and the other half, EMO scholars, including, among others, Valerie Belton, Salvatore Greco, Pekka Korhonen, Kaisa Miettinen, Serpil Sayin, Roman Słowiński, Ralph Steuer, Theo Stewart, Jyrki Wallenius, and Andrzej Wierzbicki from the MCDM community. In connection with the Second Dagstuhl Seminar, the organizers carried out a project of writing a book, covering both MCDM and EMO approaches and their hybrids. MOPGP is an international group devoted to promoting multiobjective programming (MOP) and goal programming (GP) techniques and applications. It is responsible for organizing international conferences. According to its website, it brings together the researchers and practitioners from different disciplines of optimization, operations research, mathematical programming and multi-criteria analysis. The Management Mathematics Group (MMG) organized the first international conference on “Multi-Objective and Goal Programming: Theories and Applications” (MOPGP94) at the University of Portsmouth, UK in June 1994. The group was involved in organizing the Second MOPGP Conference (MOPGP96) in collaboration with the Universities of Cordoba and Malaga, held in Torremolinos, Spain (May 1996). The MMG group was also involved in organization of the Third MOPGP Conference (31 May, 1–3 June 1998) in collaboration with Universitë Laval, Quebec City, Canada (MOPGP98). The driving force behind the

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MOPGP Conferences has been Dylan Jones and Mehrdad Tamiz, both from the University of Portsmouth. Past MOPGP Conferences have taken place in 1994, Portsmouth, UK; 1996, Torremolinos, Spain; 1998, Quebec City, Canada; 2000, Ustron, Poland; 2002, Nara, Japan; 2004, Hammamet, Tunisia; 2006, France; 2008, Portsmouth; and 2010, Sousse, Tunisia. The tradition of organizing MCDA Summer Schools for Ph.D. students started in 1983. The First Summer School was organized by Benedetto Matarazzo in Catania, Sicily that year. The most recent (Tenth) Summer School was organized by Vincent Mousseau at Ecole Centrale Paris in 2010. The number of students has varied between 40 and 60. Prominent MCDM/MCDA scholars have lectured at these events. Besides discussing recent theoretical developments, students have typically been required to solve real-world case problems with MCDA/MCDM tools. The Summer Schools have been great networking and learning experiences for Ph.D. students. Many students from previous summer schools are accomplished MCDM scholars now. The sponsoring organizations have been the International Society on Multiple Criteria Decision Making and the European Working Group on MCDA.

Multiple Criteria Decision Aid Summer School, Ecole Centrale Paris, July 2010.

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Many of us — too many to list — have, over the years, organized MCDM sessions and tracks at major conferences, such as ORSA/TIMS and INFORMS, as well as at EURO and IFORS Conferences. Several of us have also served as program chairs or organizing committee chairs for major conferences. We have also been active in fundraising to support both meetings and other activities of MCDM. Decision analysts have an active society within INFORMS. A new INFORMS Section on MCDM has been established in June 2010 to increase the visibility of MCDM in North America.

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MCDM Society Traditions

At least one of this book’s authors has attended each of the first 20 conferences of the International Society on MCDM. Stan and Jyrki both attended the first conference in Jouy-en-Josas, France as well as many others. Stan has missed only two conferences: the 18th in Chania, Greece and the 19th in Auckland, New Zealand. Jyrki has missed four of the 20 conferences. Murat’s first MCDM conference was the 6th International Conference in Cleveland, USA and since then Murat has only missed the 7th Conference in Kyoto, Japan. Stan organized the first conference together with Hervė Thiriez and the second conference in Buffalo, USA himself. Murat organized the 15th Conference in Ankara, Turkey. Jyrki is the program co-chair with Pekka Korhonen of the 21st Conference to be held in Jyväskylä, Finland, June 2011. During these conferences, a set of traditions have evolved. In the early conferences, there were many attendees from the then eastern bloc countries, an unusual occurrence at the time. Attendees usually stayed and shared rooms in student housing facilities. The local expenses of students and those coming from countries where travel support was limited were partially or totally covered by the conference organizers through funds raised from sponsors. This tradition was continued at least until the 15th Conference in Ankara. Covering local expenses for those in need of support was excellent; it permitted superb participants who would not otherwise be able, to attend conferences. There was fruitful interaction, exchange of ideas, and international collaboration. Even in the early years when east-west interactions were relatively uncommon, MCDM researchers were already sharing developments on Multiple Criteria Decision Making. (Today east-west interactions are more common.) These collaborations were accelerated during the tenure of Andrzej Wierzbicki (who received 89

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the Georg Cantor Award from the International Society on MCDM in 1992) as the Leader of the Systems and Decision Sciences Program of the International Institute for Applied Systems Analysis (IIASA) in Laxenburg, Austria, 1979–1984. This was fitting because IIASA had been founded in 1972 to bring together researchers from east and west to study problems of global impact. The first director of IIASA was Howard Raiffa, recipient of the Gold Medal of the International MCDM Society in 1998. The efforts to keep costs down and subsidize participants who have needed support have worked well in making the conferences accessible to researchers from all countries. This has an important role in sustaining the widely international nature of the membership: 1470 members from 96 different countries (as of May 12, 2010).1 It may not be easy to continue this tradition because of difficulties in finding sponsors and having conferences all over the world, sometimes in far-flung locations. However, we believe that every effort should be made to try to continue this support in order to maintain the rich international nature of the MCDM community. The highly diverse membership of the MCDM Society has also been reflected in the administration of the Society as well. Committees have included members from different countries and different geographical parts of the world. Conferences have been organized in many different countries all over the world, covering all the continents. At the Kyoto conference in 1986, organizers Hirotaka Nakayama and Yoshikazu Sawaragi had a banner made for the Society (which was then called the Special Interest Group on MCDM). The banner has been present at all conferences since then. A tradition has evolved: that the organizer of the previous conference maintains the banner and takes it to the next conference. The banner is displayed throughout the entire conference, typically in the auditorium where the opening ceremonies and plenary sessions are held. Another wonderful and unusual aspect of the International Society on MCDM has been that, so far, members have not had to pay dues. This has been possible by keeping costs down and using funds from local institutions as well as small surpluses from prior conferences as funding sources. 1

http://www.mcdmsociety.org

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During conferences, organizers have included activities to showcase the local geographical and cultural features to conference participants. Usually, one afternoon is set aside for an outing that provides participants with a memorable experience. Dining together provides participants many opportunities for interaction and possible joint research. Conference banquets have been important highlights of the conferences. There are often performances by folk dancers, as well as singing and dancing. It is common for some participants to demonstrate their own talents at the banquets. Awards and award ceremonies were introduced at the 1992 Conference and have since been an important part of the banquets. The Chairperson of the awards committee, together with the President of the Society, announces the winners and awards plaques to the recipients. Over the years, the MCDM community has grown and many young researchers from around the world have joined and remained as part of the community. There has been a steady and healthy growth in the field. Many closely related groups have also evolved. We believe that our traditions have been an important part of the MCDM community. It is important to continue these traditions and pass them on to future generations so as to maintain a vibrant and exciting field.

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Awards and Presidents

The International Society on Multiple Criteria Decision Making usually presents three awards at each meeting. The three awards are as follows (http://mcdmsociety.org/intro.html#Awards): 1. The MCDM Gold Medal 2. The MCDM Edgeworth-Pareto Award 3. The MCDM Georg Cantor Award These awards are made to individuals who have made significant contributions to the field of multiple criteria decision making in the course of their career. The contributions may be in the form of research, application, or some combination of the two. The recipients to date are as follows: MCDM Gold Medal 1992

Stanley Zionts

1994 1995 1997 1998

Oleg I. Larichev Bernard Roy Ralph E. Steuer Ralph L. Keeney Howard Raiffa Thomas Saaty Jaap Spronk William W. Cooper Murat Köksalan Theodor J. Stewart Benedetto Matarazzo Detlof von Winterfeldt

2000 2002 2004 2006 2008 2009

Edgeworth-Pareto Award

Georg Cantor Award

Po-Lung Yu Milan Zeleny Jyrki Wallenius Hirotaka Nakayama Roman Słowinski Jared L. Cohon

Pekka Korhonen Yacov Y. Haimes — Tomas Gal

Alexander Lotov — Raimo P. Hämäläinen James S. Dyer Kalyanmoy Deb Gwo-Hshiung Tzeng

Philippe Vincke Masatoshi Sakawa Harold P. Benson Carlos Romero Valerie Belton Yong Shi

93

Andrzej P. Wierzbicki

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The Presidents of the Society The presidents of the society to date and their terms are as follows: Stanley Zionts, State University of New York at Buffalo, USA, 1979–1992 Ralph Steuer, University of Georgia, USA, 1992–1996 Pekka Korhonen, Helsinki School of Economics, Finland, 1996–2000 Valerie Belton, University of Strathclyde, United Kingdom, 2000–2004 Theo Stewart, University of Cape Town, South Africa, 2004–2008 Jyrki Wallenius, Aalto University School of Economics, Finland, 2008–2011 Kaisa Miettinen, University of Jyväskylä, Finland (President Elect for 2011–2015)

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Chapter 8

Biographies of Leading MCDM Scholars*

David E. Bell was born in Doncaster, England in 1949. In 1971 he received a B.A. in Mathematics from Merton College, Oxford and in 1973 a Ph.D. in Operations Research from MIT, with a dissertation on integer programming titled “The Resolution of Duality Gaps in Discrete Optimization.” He then spent two years at IIASA as one of their first research scholars, working with the likes of Howard Raiffa and George Dantzig. He also co-organized the first IIASA Workshop on MCDM in 1975. He attended the MCDM David Bell conferences at Buffalo (1977) and in Delaware (1980) where he gave his first presentation about utility and regret. In 1977 he joined the Harvard Business School faculty where he is now the George M. Moffett Professor of Business Administration. During his time on the Harvard faculty he has taught MBA and executive courses on managerial economics, risk management, marketing, retailing, and most recently, agribusiness. Following six years as head of the school’s marketing department he is currently Senior Associate Dean with recruiting responsibilities.

* Although we asked people where possible to give us biographical sketches of one-to-two pages in length, in several cases we were unable to do any better than the short sketches that we have included. 95

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David’s research has mostly dealt with utility theory; indeed twelve of his papers contain the word “utility” in the title. Though he had read Howard Raiffa’s seminal book on decision analysis while at Oxford, it was at MIT, where he wrote a master’s thesis under Ralph Keeney that he really became fascinated with the topic of decision making. While much of his work has centered on decomposing utility functions with a view to simplifying their assessment (e.g., interpolation independence and the one-switch rule), he is best known for his papers highlighting the importance of psychological factors like regret and disappointment in risky decision making. David, with his colleague Arthur Schleifer Jr., produced a series of textbooks on managerial decision analysis including Decision Making Under Uncertainty; Data Analysis, Regression and Forecasting; and Risk Management. David was Program Chair of the 1985 ORSA-TIMS Conference in Boston and has been Departmental Editor for Decision Analysis for both Operations Research and Management Science. In 2001 he was awarded the Ramsey Medal by the Decision Analysis Society of INFORMS. David and his wife Stacey have three children and one grandchild. Having recently hung up his squash racket, he is currently researching his Yorkshire and Devon roots. Valerie Belton was born on August 9, 1956. She received her B.Sc. degree in Mathematics from Collingwood College, Durham University, UK, her M.A. degree in Operational Research from Lancaster University, UK, and her Ph.D. degree from Cambridge University, UK. Valerie Belton is currently a professor of Management Science and the Vice Dean of the Business School at University of Strathclyde, UK. Valerie’s research interests have been Valerie Belton focused on multiple criteria decision analysis (MCDA). She has particularly been interested in visual interactive modeling, problem structuring, and applications of MCDA in practice.

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Valerie has been active in professional societies. She served as the President of the International Society on MCDM and is currently the President of the European Federation of OR Societies (EURO). She was the Editor of the Journal of Multicriteria Decision Analysis from 2000 to 2009 and she served as a guest editor of several special issues for various journals. She has also been involved in the organization of various conferences and was the conference chair for EURO XIII, 1994. Valerie Belton received the Wiley Prize in Applied MCDM in 1995 and the Georg Cantor Award from the International Society on MCDM in 2008. Valerie enjoys orienteering, mountain marathons, and mountain bike orienteering. Harold Philip Benson was born on August 23, 1949, in Atlanta, Georgia, USA. From an early age, he showed an interest and talent for mathematics. His older brother noticed this, and he joked that when Harold grew up, he wanted to be a computer! Indeed, Harold went on to the University of Michigan, Ann Arbor, where he obtained his B.Sc. degree in Mathematics with Highest Honors in 1971. Throughout his undergraduate years, while he enjoyed mathematics, Harold was looking for suitable and Harold Benson interesting applications of mathematical methods. In his senior year at the University of Michigan, Harold took a course in linear programming. The professor of the course, which was taught in the Business School, called his students “refugees from the math department.” And he was right. They all wanted to study applications of mathematics, not just the theory of mathematics. This linear programming course inspired Harold to continue his studies at the graduate level, but in Industrial Engineering and Management Sciences at Northwestern University. There, he earned his M.Sc. and Ph.D. degrees, in 1973 and 1976, respectively. His advisor at Northwestern was

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Professor Thomas L. Morin, an outgoing, open-minded fellow who allowed Harold almost free reign in picking a dissertation topic. Harold eventually chose the topic “Nutrition Planning in Developing Nations: A Bicriteria Mathematical Programming Approach.” Harold went on to be a visiting assistant professor for one year at the University of Illinois, Champaign-Urbana, after which he worked as a researcher for three years at General Motors. Since 1979, he has been a professor at the University of Florida’s Warrington College of Business Administration. Sometimes Harold’s classes are large, so large that many courses are televised. Once, Harold’s son Stephen, who was ten years old at the time, was watching his dad give a lecture on television. Stephen proclaimed, “I have always been wanting to do this,” at which point he pressed the mute button! Harold’s publishing career began in 1977. Since then, he has published 75 refereed articles and book chapters, 36 of which are in the MCDM area. The remaining 39 non-MDCM papers are in various areas of optimization, predominantly global optimization. Most MCDM papers deal with theory, solution methods and applications of multiple objective linear programming (MOLP) and multiple objective nonlinear programming (MONLP). Highlights of his MCDM contributions include introducing, defining and studying an improved definition of proper efficiency in MONLP; studying the existence of efficient solutions in MONLP; introducing and studying the domination property with respect to cones in MONLP; introducing, studying the theory of, and creating algorithms for the problem of optimizing over the efficient set; introducing new ways to detect complete efficiency in MONLP and MOLP. He has also worked on generating the complete set of efficient points and extreme point efficient points both in decision space and in outcome space of an MOLP, and showing how to pivot in an outcome polyhedron. Further he has shown how to apply MOLP and MONLP to various realworld problems, including nutrition planning, citrus rootstock selection, and surgery scheduling. Harold holds or has held associate editorships in a variety of journals, including the Journal of Optimization Theory and Applications, the Journal of Global Optimization, Naval Research Logistics, Operations Research Letters, and the Journal of Mathematical Analysis and

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Applications. He also serves on the editorial boards of four other international journals. For his outstanding contributions to the theory, methodology, and practice of MCDM, Harold received the Georg Cantor Award in 2004 from the International Society on MCDM. He has also received many teaching awards from the University of Florida. His former Ph.D. students include Yasemin Aksoy, Serpil Sayin, Erjiang Sun and several others, many of whom have gone on to have successful careers involving MCDM work and research. Harold lives in Gainesville, Florida, with his loving wife Suzanne and his younger son Chaz. His older son Stephen is pursuing a Ph.D. degree at Yale. Harold also enjoys playing the piano and organizing and listening to his music collection. Denis Bouyssou was born on December 12, 1960. He received a Bachelor’s degree in Law from Université Paris X Nanterre in 1981, and an M.B.A. degree from the ESSEC business school in 1980. In addition he received a M.Sc. in Scientific Methods of Management and a Ph.D. in Decision Aid Tools, in 1981 and 1990, respectively, from Université ParisDauphine. Professor Bernard Roy served as his Ph.D. thesis supervisor. Denis was Professor of Decision Sciences at ESSEC from 1987 to 2001. He Denis Bouyssou has served as a CNRS research director at the LAMSADE Research Center at Université Paris-Dauphine since 2001. Denis has published extensively in such areas as preference modeling and aggregation, utility theory, outranking methods, and axiomatic development of multi-criteria methods. He has held many editorial positions including that of the Co-Editorin-Chief of 4OR. He held various administrative positions in professional societies and served as the secretary of EURO from 1994 to 1998. Denis likes hiking, especially in such locations as the Alps, Corsica, and the Pyrenees.

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Abraham Charnes (1917–1992) was born on September 4, 1917, in Hopewell, Virginia. He received Bachelor’s, Master’s, and Ph.D. degrees from the University of Illinois in 1938, 1939, and 1947, respectively. Though Charnes had accepted a graduate scholarship at Harvard University, World War II interrupted his Harvard studies. During World War II Charnes served in the US Navy as a research physicist and operations analyst. For his contributions, he received the Distinguished Public Service medal from the US Navy. Abraham Charnes Abraham Charnes began his academic career in 1947 as Assistant Professor of Mathematics at the Carnegie Institute of Technology. Later he taught at Purdue University and Northwestern University. At Northwestern he was the Walter P. Murphy Professor of Applied Mathematics. Charnes joined the University of Texas at Austin in 1968, where he held the Jesse H. Jones Professorship and was a University System Professor. He was later named John P. Harbin Professor in the College of Business Administration. Abraham Charnes was an internationally renowned authority on developing new and advanced mathematical methods used for management problem solving in government, industry, engineering, and medicine. Abraham Charnes published eight books and 434 articles in professional journals (many with his long-time friend and colleague W.W. Cooper — the two worked together for over forty years). One of their best known works (with A. Henderson), An Introduction to Linear Programming, 1956, was translated into Chinese, Russian, and Japanese. Another publication, Management Models and Industrial Applications of Linear Programming, 1961, was translated into Czech. It contained, among other things, a description of goal programming, an extension of linear programming to deal with multiple goals. Examples of his publications include a model for blending gasolines with W. Cooper and B. Mellon published in Econometrica, 1952, one of the first LP models used in industry. Degeneracy turned out to be a problem. Hence he developed a remedy, which completed the theoretical development of the simplex

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method. (“Optimality and Degeneracy in the Simplex Method,” Econometrica, 1952.) With Bill Cooper, Abraham Charnes solved the general linear fractional programming problem, making possible their development of data envelopment analysis two decades later. In 1975 Abraham Charnes was a finalist for the Nobel Prize in Economics. He was the recipient of many honors, including the John von Neumann Theory Prize of the Institute of Management Sciences and the Operations Research Society of America, and the Harold Lardner Memorial Award from the Canadian Operations Research Society. Charnes and William W. Cooper were awarded the INFORMS Impact Prize in 2006. Charnes died in Austin, Texas, December 19, 1992, at the age of 75. The Kay and Abraham Charnes Endowed Presidential Scholarship at the University of Texas’ McCombs School of Business has been set up in memory of Professor and Mrs. Charnes. Jared L. Cohon was born on October 7, 1947 in Cleveland, Ohio. He received his B.Sc. in Civil Engineering from the University of Pennsylvania in 1969. He became interested in environmental problems while taking a course as an undergraduate. He received his Ph.D. in Civil Engineering from MIT in 1973 where he was David Marks’ first doctoral student. Although he was in a Civil Engineering program, his interest was more in the application of mathematics to environmental issues. He took many courses in Economics Jared L. Cohon and Operations Research and went out to write his dissertation in Multiobjective Programming. He then published a pioneering book on Multiobjective Programming in 1978 based on his dissertation work; the book was selected as a “classic” in operations research and was republished by Dover Press in 2003. Jared Cohon served as a professor of Geography and Environmental Engineering at Johns Hopkins University from 1973 to 1992. During this period, he also took on administrative duties as Assistant and Associate

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Dean of Engineering and Vice Provost for research. He then became the Dean of the School of Forestry and Environmental Studies at Yale University where he served from 1992 to 1997. Jared was named President of Carnegie-Mellon University in 1997 and is currently serving his third five-year term. Jared has been interested in interdisciplinary research areas. He has worked on large-scale problems having important environmental impact, including water resource management and energy facility location. He has approached problems from a multiobjective and interdisciplinary perspective, and published extensively in these areas. He took a leave from teaching in 1977 and 1978 to serve as the first Legislative Assistant for Energy and Environment to the now-deceased Senator from New York, Daniel Patrick Moynihan. Jared was appointed in 1995 by President Bill Clinton as a member of the US Nuclear Waste Technical Review Board and as its Chairman in 1997. His term on the Board ended in 2002. President George W. Bush appointed Jared to the Homeland Security Advisory Council in 2002; President Barack Obama reappointed him in 2009. Jared has chaired or served on many committees of the US National Academy of Sciences. Most recently, he chaired the committee that produced the report, “The Hidden Costs of Energy” which was requested by the US Congress. The report provides estimates of the monetary value of the externalities associated with energy use in the United States. The awards Jared Cohon has received include the Joan Hodges Queneau Medal for outstanding engineering achievement in environmental conservation from the American Association of Engineering Societies and the National Audubon Society in 1996, the Edgeworth-Pareto Award from the International Society on Multiple Criteria Decision Making in 1998, and the William Metcalf Award from the Engineering Society of Western Pennsylvania in 2006. In 2009 he was named a Distinguished Member of the American Society of Civil Engineers. Jared lives in Pittsburgh with his wife Maureen, a leading family law attorney who has been a pioneer in providing legal services to same-sex couples. Their daughter, Hallie Donner (a celebrated teacher, producer and director of children’s theater), their son-in-law, Josh Donner (a leader in providing social services to the Jewish community) and their grandsons, Nathan and Solomon Donner, also live in Pittsburgh.

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William W. Cooper was born July 23, 1914 in Birmingham, Alabama. Though he never graduated from high school, a benefactor, on meeting him, was so impressed with his intellect that he provided funds for Bill to attend the University of Chicago, where he graduated Phi Beta Kappa in Economics in 1938. Bill Cooper did graduate work at Columbia University (1940–1942). After completing his formal education, he worked at the Tennessee Valley Authority, the US Bureau of the Budget and the University of Chicago. He William Wager Cooper joined the Carnegie Institute of Technology (now Carnegie-Mellon University) in Pittsburgh in 1946 and became one of the founding fathers of the Graduate School of Industrial Administration there. Herbert Simon’s memoirs Models of My Life, MIT Press, 1996, contains an interesting discussion about how Bill Cooper, Herbert Simon, Lee Bach and Provost Smith did it. They perceived American business education (at the time) as a “wasteland of vocationalism that needed to be transformed into science-based professionalism, as medicine and engineering …” Bill Cooper became the founding Dean of the School of Urban and Public Affairs (now in the H. John Heinz III College) at Carnegie-Mellon. In 1975 he moved to the Harvard Business School, and in 1980 he moved to the University of Texas at Austin. Cooper is the Foster Parker Professor of Finance and Management (Emeritus) and the Nadya Kozmetsky Scott Centennial Fellow at the IC2 Institute in the McCombs School of Business at the University of Texas at Austin. He continues his research at an advanced age. Bill Cooper worked with Abraham Charnes doing pioneering work in numerous aspects of accounting and management science. He was the first President of the Institute of Management Sciences, a predecessor organization of INFORMS, the Institute for Operations Research and the Management Sciences. He is the author of over 25 books and more than 500 articles. He has received many awards, among them the AICPA’s (American Institute of Certified Public Accountants) first award for the most valuable article on accounting, membership in the Accounting Hall

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of Fame, and the International Society on Multiple Criteria Decision Making’s Gold Medal, as well as several honorary doctorate degrees. In 1955 Charnes, Cooper, and Ferguson published an article that contained the essence of goal programming (A. Charnes et al., 1955), even though the name goal programming was first used in Charnes and Cooper (Charnes and Cooper, 1961). Goal programming is one of the first widely accepted models of multiple criteria decision making. A. Charnes, W. Cooper and E. Rhodes wrote another important publication (essentially from Rhodes’ thesis at Carnegie-Mellon), which they published in EJOR, in 1978. This paper contained the original data envelopment analysis models, and has become (by far) the most cited of all EJOR papers (“Measuring the Efficiency of Decision Making Units,” EJOR 2 (4), 1978). Not so well known was the fact that Cooper was a prize fighter for five years. He earned money during the Great Depression to help support his family. His record was 58 wins, three losses, and two draws. He earned $25 for each fight. At one point in his career, Cooper (then in his sixties) was walking with colleagues across the Harvard campus when they were accosted by thugs. Cooper put up his fists, ready to fight the thugs, and scared them off. The William W. and Ruth F. Cooper Fellowship was set up at the University of Texas’ McComb School of Business in honor of Professor and Mrs. Cooper. Kalyanmoy Deb was born on April 29, 1962 in Tripura, India. He received a B.Sc. degree in Mechanical Engineering from the Indian Institute of Technology, Kharagpur in 1985, and his M.Sc. and Ph.D. degrees in Engineering Mechanics in 1987 and 1991, respectively, from the University of Alabama. Kalyanmoy is Professor of Mechanical Engineering at the Indian Institute of Technology, Kanpur and Director of the Kanpur Genetic Algorithms Laboratory (KanGAL) which he established in 1997. Kalyanmoy was appointed Professor at the

Kalyanmoy Deb

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Helsinki School of Economics (HSE) in 2009 after spending two years there as a Finnish Distinguished Professor. He currently holds a joint appointment between IIT Kanpur and Aalto University School of Economics. Kalyanmoy has received numerous awards, including the Thomson Citation Laureate Award in Computer Science in 2006 and The MCDM Edgeworth-Pareto Award from the International Society on MCDM in 2008. Kalyanmoy is a pioneer in the area of evolutionary multiobjective optimization (EMO). He has published extensively in this area and his work has been heavily cited. He has played an active role building bridges between the EMO and “traditional” MCDM communities. He was one of the organizers of the first Dagstuhl seminars, where EMO scholars and MCDM scholars would meet. Kalyanmoy has held editorial positions for many publications including the IEEE Transactions on Evolutionary Computation and Evolutionary Computation journals. James Dyer was born May 7, 1943 in Brownsboro, Texas, about 75 miles east of Dallas. His parents grew up on farms, and their lives had been deeply affected by the Depression. His father liked to brag that he was the valedictorian of his high school class, even though there was only one other person in his graduating class. He did finish one year at a junior college and drove a truck in the East Texas oil fields before finding a career with Commercial Credit Corporation. His James Dyer mother managed to put herself through college and was the first person in her family to graduate from college; she became a school teacher. Jim grew up in Fort Worth, Texas and was influenced by the “space race” that captured the attention of the United States in the 1950s as the Soviet Union placed satellites, dogs, and men in orbit before any US successes in space. The National Science Foundation funded programs to support science and mathematics in high school, and Jim was selected to

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participate in a six week summer program in pure mathematics at the University of Texas between his junior and senior years in high school. The program was taught by UT faculty members and included about 30 students chosen based on a competitive exam from the State of Texas. His experience in Austin was educational, but also such great fun that he did not bother to apply to any other university and entered UT as a physics major in 1961. College was a wonderful time, and he became involved in student government, school spirit organizations, and a fraternity. He received his Bachelor’s degree in Physics (1965) with honors. Jim Dyer decided to stay in Austin for graduate school as well and started in the M.B.A. program there. Early on, one of his professors recommended that he apply for a Ford Foundation Ph.D. fellowship and he received his Ph.D. in Business Administration from the University of Texas in Austin in 1969. Thinking that it would be easier to move from an academic position to a non-academic position rather than vice versa if he wanted to later, Dyer took a faculty position in the School of Management at UCLA. At UCLA Dyer had the opportunity to work with such luminaries as Elwood Buffa, Arthur Geoffrion, and Jacob Marschak. He also interacted with a number of MCDM/Decision Analysis stalwarts at the neighboring University of Southern California. In 1978 he was invited to join the faculty of the University of Texas at Austin where he has been ever since. He has held several faculty administrative positions during his tenure at the University of Texas and is now the Fondren Centennial Chair in Business at the Red McCombs School of Business Administration. Dyer’s research and teaching interests are focused on applications of decision analysis and real options to problems of risk management and capital budgeting, and he has published extensively on these subjects in various journals, including Management Science and Operations Research. He also teaches in the University of Texas’ Executive MBA programs offered in Dallas and Mexico City. He is the former Chair of the Decision Analysis Society Group of INFORMS, and served as the Area Editor for decision analysis for Operations Research. Among his honors, Dyer was awarded the Ramsey Medal by the Decision Analysis Society of INFORMS, the Edgeworth-Pareto Award by

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the International Society on Multiple Criteria Decision Making, and was named a fellow of INFORMS. In addition, he was a finalist in the Franz Edelman Award Competition of INFORMS on two occasions. Jim Dyer became interested in the petroleum industry at an early age. Reflecting this interest, he has been actively involved in a number of energy companies and the Department of Energy. He has consulted with many companies regarding the application of decision and risk analysis tools to a variety of practical problems. His clients have included Amoco, Texaco, ENI, Schlumberger, Petrobras, Pemex, Standard Oil of Indiana (merged into BP), and the Department of Energy. Now that his two sons are grown and have provided him and his wife with four granddaughters and a grandson, Jim is actively involved in the grandchildren’s soccer games and other activities. Jim and his family also enjoy taking their dog to the Austin Hill Country to enjoy bird hunting. Ward Edwards (1927–2005) was born in Morristown, New Jersey, April 5, 1927. He is generally regarded as the father of behavioral decision research. After studying psychology at Swarthmore College, he went to Harvard to do his Ph.D. where he studied under Professor Charles Frederick Mosteller, one of the most eminent statisticians of the 20th century, graduating in 1953. He published two seminal articles, creating behavioral decision research as a new field in psychology, one in 1954 and the other in 1961. In his 1954 Ward Edwards Psychological Review article he introduced the expected utility model to psychologists and posed the (good) question: do people actually behave this way? However, it was first the publication of Ward Edward’s 1961 Annual Review of Psychology paper that established the field of behavioral decision making. According to Lawrence D. Phillips and Detlof von Winterfeldt (2007), the paper discussed issues such as how people make decisions and how they can be improved. Two years

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later Edwards ‘with two colleagues’ published another very influential paper, “Bayesian Statistical Inference for Psychological Research,” in Psychological Review (Edwards, Lindman, and Savage, 1963). He was thrilled about the Bayesian view. During this period, Ward Edwards and his students conducted several experimental studies to determine how well the Bayesian model described human behavior. Ward Edwards was also interested in multiattribute utility theory. He developed a simpler version of it, called SMART (1971, 1977). Ward Edwards also applied his approach to social (or societal) problems. Furthermore, he was one of the first to discuss the subjective expected utility (SEU) model, where the subjective probabilities do not have to obey the axioms of probability (“Subjective Probabilities Inferred from Decisions,” Psychological Review, 1962). According to Jerome R. Busemeyer from Indiana University, Edwards’ theory was more general than Kahneman-Tversky prospect theory. Detlof von Winterfeldt (who was one of Ward’s Ph.D. students) and Ward Edwards published a well known book, Decision Analysis and Behavioral Research, in 1986, which became a must-read for graduate students in behavioral decision making. According to Phillips and von Winterfeldt, after his retirement in July 1995, Ward remained active in many projects, but because he had been suffering from Parkinson’s disease for many years, his energy was increasingly limited. .

Peter Clingerman Fishburn was born on September 2, 1936 in Philipsburg, Pennsylvania. He grew up in State College where his father was Chair of the Music and Music Education Departments at Penn State. He graduated from Penn State in 1958 with a degree in industrial engineering. At Penn State he was a member of the Blue Band and President of Lion’s Paw, a men’s leadership honorary. He and Janet Forsythe were married in 1958. They have three daughters and now live in retirement in Basking Ridge,

Peter Fishburn

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New Jersey. His hobbies are gardening, bird watching, playing his cornet and Scrabble. Peter enrolled in the operations research program at the Case Institute of Technology where he earned his Ph.D. in 1962. From 1962 to 1969 he lived in Potomac Maryland and worked at the Research Analysis Corporation in McLean Virginia. In 1967 he and his family enjoyed living in Denmark for a semester when he was appointed as a Fulbright Professor at the Technical High School (college) near Copenhagen. During that time he gave lectures in Denmark, Italy, Belgium and England. After a year at the Institute for Advanced Study in Princeton, New Jersey, the family moved to State College, Pennsylvania in 1971 where Peter was appointed Research Professor of Management Science and Janet earned a Ph.D. in American Religious Studies. This was followed by a move back to New Jersey where Janet was appointed to the faculty of Drew University and Peter was hired by the economics and mathematics groups at Bell Labs in Murray Hill. Janet retired in 1995 and Peter retired in 2001. Peter is the author or co-author of nine books and more than 500 journal articles. During his distinguished career he produced many seminal contributions to utility and value theory, as well as to social choice theory. He is a Fellow of the Econometric Society, the Institute of Mathematical Statistics, and INFORMS. In 1987 Peter received the Frank P. Ramsey medal from the Operations Research Society of America, and in 1996 he was awarded the John von Neumann Theory Prize of INFORMS. The Mathematics of Preference, Choice and Order (ed. by Steven Brams, William Gehrlein and Fred Roberts) was published in 2009 to honor Peter. Peter Fishburn’s Erdös number is 1; he co-authored two papers with Paul Erdös, the famous Hungarian mathematician. Erdös was one of the most prolific mathematicians of the 20th century. His friends started (playfully) to measure “collaborative distance” to him by inventing the Erdös number. A person’s Erdös number is equal to 1, if he or she has co-authored a paper with him (Erdös). Persons who are co-authors with the co-authors (but not with Erdös) have Erdös number 2, and so on.

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Tomas Gal was born in Zilina in the former Czechoslovakia in 1926. In September 1944 during World War II, he was sent to the Auschwitz-Birkenau concentration camp by the fascist Slowak government. After being freed he continued his studies in Physical Chemistry at the Karlsuniversität, Prague. From 1954 to 1964 Gal worked as an assistant in mathematics for the Landwirtschaftlichen Hochschule Prague. From 1964 to 1969 he served as Professor for the newly founded Tomas Gal “Lehrstuhl für Lineare Programmierung.” After that he worked as a visiting professor for a year at the Center for Operations Research and Econometrics (CORE), in Louvain, Belgium. After that he did not return to Czechoslovakia. From 1970 to 1977 Gal was Professor at RWTH, Aachen, Germany, and since 1977, Professor of Operations Research at the Fernuniversität, Hagen. Tomas Gal retired as Emeritus Professor from Fernuniversität in 1991. Tomas Gal co-organized with Günter Fandel, the Königswinter MCDM Conference in Germany in 1979 and the Hagen MCDM Conference in 1995. Tomas Gal did seminal research in sensitivity analysis, parametric programming, and degeneracy, concepts which he then generalized to MCDM. Tomas Gal published more than 100 articles in sensitivity analysis, parametric programming, MCDM, vector maximization, and redundancy in linear programming, including several Management Science publications. More recently, he worked with his friend and colleague Günter Fandel, on two papers dealing with resource allocation in a university setting, resulting in two EJOR papers. He supervised eight Ph.D. dissertations during his time in Hagen. In 1991, Günter Fandel and Hermann Gehring edited a volume in honor of Tomas Gal’s 65th birthday: Operations Research – Beiträge zur quantitativen Wirtschaftsforschung. During his career Tomas Gal published in three languages: English, German, and Czech. He was awarded the Cantor Award by the International Society on Multiple Criteria Decision Making in 1998.

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Arthur M. Geoffrion was born in Brooklyn, NY on September 19, 1937 and grew up in Manhasset, Long Island. As a child, he had many interests, these included adventure radio programs, hypnotism, atomic energy, amateur radio, golf, baseball and rooting for the Brooklyn Dodgers. Art Geoffrion majored in Mechanical Engineering at Cornell because he felt an obligation to be able to work in and possibly take over his father’s watch case manufacturing business. He found that he had little Arthur Geoffrion aptitude for mechanics and lost interest completely after discovering operations research during his junior year at Cornell. He liked the idea of helping people make optimal decisions. He stayed long enough at Cornell to complete a Master’s degree in Industrial Engineering, which was as close as Cornell got to OR at that time. He joined the Ph.D. program in Industrial Engineering at Stanford primarily because he had been impressed by Stanford University Professor Gerald J. Lieberman, whom he had visited during Lieberman’s sabbatical at Columbia. When Stanford created a Ph.D. program in Operations Research, Art transferred into it as its first student. Lieberman was Art’s academic advisor, and Harvey Wagner was his dissertation advisor. Art proposed several different Ph.D. dissertation topics, finally settling on one involving multiple criteria (A Parametric Programming Solution to the Vector Maximum Problem with Applications to Decisions Under Uncertainty, Ph.D. thesis, Stanford University, 1965). Art Geoffrion joined the UCLA School of Business faculty after completing his degree. For his first eight years there, he benefited greatly from interactions with an excellent second set of OR colleagues as a consultant to the RAND Corporation. His dissertation led to additional work in MCDM, but Geoffrion gradually turned to a more algorithmic direction centered on single-objective integer programming and largescale programming. He then went on to work on applications that were not explicitly multi-criteria, but usually tried to take account of the

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importance of multiple criteria through other means. He was named the James A. Collins Professor of Management in 1998. Art Geoffrion is the author of more than 60 published works, initially on mathematical programming and its applications, including topics in decomposition techniques for special structures, duality, integer programming, Lagrangean relaxation and multicriteria optimization. He has consulted extensively on applications of optimization to problems of distribution, production and capital budgeting. In 1978 he co-founded INSIGHT, Inc., a management consulting firm specializing in optimization-based applications in supply-chain management and production. In 1982 he founded what is now the INFORMS Roundtable, an organization composed of the leaders of operations research groups in 50–60 companies. During the 1980s, his interests shifted to the foundations of modeling, modeling formalisms and computer-based modeling environments as an approach to improving the quality, productivity and acceptability of model-based work. Since the mid-1990s, his interests have centered on the implications of the Internet and digital economy for management and management science. His editorial service includes eight years as Department Editor (Mathematical Programming and Networks) of Management Science, positions at Mathematical Programming and J. Association of Computing Machinery, and several editorial advisory boards. He was President of the Institute of Management Sciences (TIMS — a predecessor organization of the Institute of Operations Research and Management Science (INFORMS)) from 1981 to 1982 and President of INFORMS in 1997. His many honors include being awarded the honorary degree of Doctor Honoris Causa by the RWTH Aachen University in 2005, the NATO Systems Science Prize in 1976, the TIMS Distinguished Service Medal, 1992, and the George E. Kimball Medal (INFORMS), 2000. He was also named a National Academy of Engineering member, a Fellow of the International Academy of Management, and a Fellow of INFORMS. Art retired at the end of 2005. Since then, he has been active in service to the National Academies, INFORMS, UCLA, two non-profit organizations, and the first four schools he attended. He also runs websites for four affinity groups, is passionate about family history research and

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related projects, and enjoys spending time with his wife, two children, and five grandchildren. Yacov Y. Haimes was born in Baghdad, Iraq on June 18, 1936. Because of a pogrom against the Jews in Iraq, he was smuggled across the northern border of Iraq into Iran when he was 13 years old. He stayed in Tehran for four months, and then went to Israel via Cyprus. Haimes continued his education at Ben-Shemen, an agricultural boarding school and then moved to Tel Aviv to complete his high-school education. After completing high school, he served for threeand-a half years in the Israeli Army as a Yacov Haimes platoon tank commander. After his military service, Yacov enrolled at the Hebrew University of Jerusalem and graduated in 1964 with a B.Sc., majoring in Mathematics, Physics, and Chemistry. From 1963–1965 he worked part-time as a Junior Petroleum Engineer in the Israeli Ministry of Development. In 1965 he moved to the US for graduate work at UCLA. He received his M.Sc. in Systems Engineering in 1967 and his Ph.D. in Large-Scale Systems Engineering with Distinction in January 1970, both from UCLA. He has minors in Water Resource Systems Engineering and Control Systems Engineering. Haimes joined the Systems Engineering faculty of Case Western Reserve University in February 1970, where he later served as Chair of the Department. During his 1977–1978 sabbatical year, Haimes was an AAAS1/American Geophysical Union Congressional Science Fellow, joining the staff of the Executive Office of President Jimmy Carter, and later the staff of the House Science and Technology Committee. Over the years he has held several offices as President and Chair of boards of directors of professional and public service organizations. He has also

1

The American Association for the Advancement of Science.

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organized a number of national and international professional society conferences. Yacov Haimes’ research interests include risk-based decision making, multiobjective trade-off analysis, and hierarchical analysis of large-scale systems. He has applied his research results to problems of water resources and environmental and industrial systems. He has had an extensive amount of sponsored research. He is a professional engineer in two states: Ohio and Virginia. In 1987 he joined the Systems Engineering faculty of the University of Virginia and shortly thereafter founded the University-wide Center for Risk Management of Engineering Systems. Since its founding, Haimes has served as its Director. During his tenure as professor on the faculties of both universities, Haimes has served as Ph.D. dissertation advisor to 35 graduate students and as M.Sc. thesis advisor to over 70 graduate students. He has authored two books, co-authored four books, and edited over 20 volumes. The third edition of his latest book, Risk Modeling, Assessment, and Management, was published in 2009. His classic book with Vira Chankong, Multiobjective Decision Making: Theory and Methodology, was first published in 1983 and republished in 2008 by Dover Publications. He is the author of 300 papers, 200 of which are in archival-referred journals. Haimes’ many honors and awards include being named a Fellow of the International Council on Engineering Systems, a Fellow of the Society for Risk Analysis, a Fellow of the American Water Resources Association, a Fellow of the International Water Resources Association, a Fellow of the American Association for the Advancement of Science, a Fellow of the Institute of Electrical and Electronics Engineers, a Fellow of the American Society of Civil Engineers, and the Arthur MaassGilbert White Fellow, US Army Institute for Water Resources. He has been awarded the Georg Cantor Award by the International Society on Multiple Criteria Decision Making, as well as many other prestigious awards. Yacov Haimes is also active in non-profit organizations in Charlottesville, VA. He is married to Sonia and the couple has two children.

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Raimo P. Hämäläinen was born in Helsinki, July 7, 1948. He received his schooling in Helsinki from the same elite high school as Jyrki Wallenius, although Raimo was senior by a year. All his degrees are from the Helsinki University of Technology (HUT), where he earned his doctorate in Applied Mathematics in 1977, with the dissertation “Optimal Controller Design by Nonlinear and Game Theoretic Methods.” He has a systems and control theory background similar to many of the Raimo P. Hämäläinen early MCDM pioneers. Raimo Hämäläinen was appointed Professor of Applied Mathematics at the Helsinki University of Technology in 1981. Hämäläinen has devoted his energies to founding the Systems Analysis Laboratory at HUT and making it into a world-class research and educational unit. He has supervised over 30 Ph.D. dissertations and numerous Masters theses. Hämäläinen is perhaps best known for his work in dynamic games and decision analysis. He is one of the founding members of the International Society for Dynamic Games (ISDG) established in Helsinki in 1990, hosting the society’s secretariat for many years. While Raimo Hämäläinen was active in dynamic game theory, he also wanted to conduct research in decision modeling. His goal was to help practical decision making. This is how he came across decision analysis. As a first case study he helped the Parliament of Finland decide about a nuclear power plant license in 1984. Hämäläinen is a prolific writer (often with his Ph.D. students or former Ph.D. students). He is the author or coauthor of more than 180 publications on decision making, optimal control, dynamic games, energy modeling, environmental decision making, group decision making, and biological systems. In addition to math, he has studied physiology and developed models for human respiratory and cardiac functions. He has also designed widely used decision support software, including several web-based systems. He is Director of the National Graduate School on Systems Analysis, Decision Making and Risk Management. As a consultant he has helped solve problems in several areas including environmental policy and risk

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analysis. Recently he has worked on the concept of systems intelligence with Philosophy Professor Esa Saarinen, a friend and colleague at HUT. Raimo has spent many sabbaticals abroad, mostly in the US, mainly in California. The Board of the Finnish Operations Research Society appointed Raimo Hämäläinen its Honorary President. The International Society on Multiple Criteria Decision Making presented the EdgeworthPareto Award to him in 2004. Raimo enjoys outdoor activities such as fishing, mushroom and berry picking, sailing (especially competitively), tennis, and snow boarding, as well as visits to two of his summer cottages. He has two sons. Mark H. Karwan was born in Cleveland, Ohio in 1951. His father sorted mail for the US Postal Service and his mother was a (head) nurse. After spending his early years living with grandpa Stanley Karwan, Mark and his family moved to a small house within 1/4 mile of the Cleveland Hopkins International Airport when he was five years old. Mark and his older brother Kirk often walked to the airport to look at the bigger and bigger new planes as they emerged on the scene. Kirk led Mark to take up many indoor Mark H. Karwan and outdoor sports including basketball, baseball, track, tennis and golf. Mark was about 12 when he became a caddy at a golf course, even earning a ‘caddy scholarship’ to help with his undergraduate education at the Johns Hopkins University. Perhaps it was the familiar ‘Hopkins’ name from the nearby airport that helped him feel comfortable with his school choice (notwithstanding the fact that Kirk was already there). His caddy and playground instructor jobs helped pay for college where he met the love of his life, Sabina Matarazzo, and further developed his love of singing; together, they performed with the University Glee Club and Chorus, as well as the Baltimore Opera Chorus. Joining Hopkins at 18, Mark left with a B.Sc. and M.Sc. in Mathematical Sciences in four years and two years later, completed his Ph.D. at Georgia Tech at age 24.

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After completing his Ph.D., he began his (ongoing) 34-year career on the faculty of the Department of Industrial Engineering at the State University of New York (SUNY) at Buffalo in 1976. Mark’s time at the SUNY can be summarized as follows. Now the Praxair Professor in Operations Research and a SUNY Distinguished Teaching Professor in the (renamed) Department of Industrial and Systems Engineering, Mark served as Chair of the department from 1987–1992 and as Dean of the School of Engineering and Applied Sciences at the University at Buffalo from 1994–2006. He has developed broad expertise in the area of mathematical programming — modeling and algorithmic development. His 24 Ph.D. students have been guided in areas of algorithmic development in integer programming, multiple criteria decision making and ‘mixed’ areas such as integer/nonlinear or integer/multi-criteria. His 80+ publications show diverse application areas such as logistics, production planning under real time pricing, capacitated lot-sizing, hazardous waste routing and security, and military path planning. Techniques to solve these problems come from the fields of linear, nonlinear and integer programming. Funding has come from NSF, ONR, AFRL2 and industry. His industry consulting experience has largely been in two fields: (1) the industrial gas industry in all areas of production planning, routing, forecasting and energy use planning and (2) supporting defense contractors in military operations research focused on logistics and dynamic resource allocation. He has won multiple teaching awards including the (SUNY) Chancellor’s Award for Excellence in Teaching and has been named a SUNY Distinguished Teaching Professor. Mark’s first Ph.D. student Bernardo Villarreal introduced him to Stan Zionts and this marked the start of a long collaboration of co-advising Ph.D. students with Stan on MCDM topics. Other joint Ph. D. students were Murat Köksalan, R. Ramesh, Hae Wang Chung, Srinivas Prasad, Vahid Lotfi, and Eleazar Puente. Mark and Sabina live in Buffalo in the same house they moved into in 1977, where they raised four wonderful and amazing children and where they love to entertain their six adorable and obviously brilliant grandchildren. 2

National Science Foundation, Office of Naval Research, Airforce Research Laboratory.

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Ralph L. Keeney was born in 1944 in Lewistown, Montana. Proud of the city in which he grew up, he says that Lewistown is the metropolis in the center of Montana with a population of about 7000. It is the largest city for over 100 miles in every direction. He has a B.Sc. in Engineering from UCLA, a M.Sc. in Electrical Engineering, and a Ph.D. in Operations Research, both from MIT. While working on his Ph.D., he worked for the Bell Telephone Laboratories as a member of their technical staff. On completing his Ralph L. Keeney degree, he taught at MIT for three years, then at Boston University’s European Graduate Program in Heidelberg, Germany for one year, prior to returning to MIT for another year. Then in 1974 he joined the International Institute for Applied Systems Analysis (IIASA) in Laxenburg, Austria as a Research Scholar. On returning from IIASA in 1976, he joined Woodward-Clyde Consultants, where he stayed for seven years. Subsequently, he joined the faculty of the University of Southern California as a professor of business and systems engineering, and in 2002 he joined the faculty of Duke University as a research professor of business. Ralph Keeney is well known for his research — both theoretical and practical. He is the author of many widely respected books and articles on various aspects of decision analysis and multiple criteria decision making. Ralph Keeney’s areas of expertise are decision analysis, risk analysis, and management decision making. He is an authority on decision making with multiple objectives. During his professional career, Ralph Keeney has contributed substantially toward the development of decision analysis and risk analysis. His experience includes corporate management problems, risk analyses, energy policy, large-scale siting studies (e.g., airports, power plants), and environmental studies. Keeney has been a consultant for several organizations in different countries, including the US, Canada, Mexico, and Germany. Among his many awards and honors, Keeney has been made a Fellow of INFORMS and the Society for Risk Analysis. He has been awarded the Gold Medal by the International Society on Multiple Criteria Decision Making. He

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has also been elected a member of the National Academy of Engineering. He was awarded the Hermes Award from the Faculty of Administrative Sciences of Laval University for exceptional contributions to multiattribute utility theory. He is a recipient of the Ramsey Medal awarded by the Decision Analysis Society of the Institute for Operations Research and the Management Sciences (INFORMS) for distinguished contributions in decision analysis, as well as the Lanchester Prize of an INFORMS predecessor, the Operations Research Society of America. His publications have received numerous awards for their applications, exposition, and contributions. Howard Raiffa and other colleagues have said that, more than anyone they know, Keeney follows the guidelines that he professes. Specifically, for any important decision, he follows the principles of value-focused thinking in structuring a problem and decision analysis in analyzing it. It is useful to get one’s thinking and feeling into alignment. It is important to really understand objectives (not a trivial exercise). Ralph lives in San Francisco with his wife Janet, who is the managing partner of a marketing and strategy consulting firm. They have one son Greg who recently graduated from college and is pursuing opportunities in the business world. For recreation, two of Ralph Keeney’s favorite active interests are playing squash and downhill skiing. In addition, his family also enjoys traveling and living in different countries. Murat Köksalan was born in Ankara, Turkey, on April 8, 1956. He was a good student in high school. He was interested in sports and was a member of the table tennis team. He enjoyed participating in many regional and national tournaments. Murat received his B.Sc. degree from the Industrial Engineering (IE) Department of the Middle East Technical University (METU) in 1979. Industrial Engineering has always been a very popular field in Turkey. When he started studying for his M.Sc. degree in the Murat Köksalan same department, he also started working as a research assistant at the System Sciences Research Institute (SIBAREN)

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under the leadership of Professor Halim Doğrusoz, who was the founder of the institute and the pioneering force behind the progress of operations research in Turkey. Professor Doğrusoz, at the age of 88, still teaches a graduate course every year at the IE Department of METU. Murat was involved in an applied project in SIBAREN as a student. After several months of working at SIBAREN, he was asked to join the IE Department as a teaching assistant with the full responsibility of teaching a juniorlevel operations research course. He accepted the position and taught the course during the second semester of his M.S. studies. He enjoyed both teaching and research during this time so much that he decided to pursue an academic career. He had always been a good student, but he became an exceptionally good student after making this decision. Thinking that single-objective models did not represent many decision problems well, he developed an interest in multiple criteria decision making. He did his M.Sc. thesis on fuzzy multiobjective programming, a new subject at the time. He completed his M.Sc. degree in 1980. Meanwhile, he won a Fulbright scholarship to pursue a Ph.D. in the United States. Murat was admitted to the Ph.D. program of the IE Department of the State University of New York at Buffalo. Soon, he started his research on multiple criteria decision making with his supervisors Mark Karwan and Stan Zionts, who had been jointly supervising Ph.D. students on MCDM. Murat developed interactive approaches for discrete multiple criteria problems having different types of criteria. He recalls with pleasure, the creative weekly meetings he had with Mark and Stan throughout the process of completing his dissertation. He completed his research in 1983 and stayed an additional year in the same department as a visiting assistant professor. Murat returned to the IE Department of METU as an assistant professor in 1984 and is currently a professor in the same department. He spent a total of five years as a visiting professor at the Krannert School of Management at Purdue University on several occasions and has been a visiting professor at the Helsinki School of Economics and the Helsinki University of Technology many times. He spent the 2010–2011 academic years as a visiting professor jointly at the Helsinki University of Technology and Helsinki School of Economics, which have merged as part of Aalto University. Murat’s current research interests include multiple criteria decision making, combinatorial optimization, multiobjective evolutionary algorithms,

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and applications. He has been involved in many company-sponsored applied projects, many of them through SIBAREN. He enjoys developing case study material for teaching purposes. He entered and won the INFORMS Case Competition three times with cases he developed together with co-authors. He was also awarded the young researcher award of the Turkish Scientific and Technical Research Council in 1992 and the MCDM Gold Medal of the International Society on MCDM in 2006. He received the Outstanding MBA Core Teaching Award at Purdue University in 2002 and the Educator of the Year Award at the Middle East Technical University in 2009. Murat attended his first International MCDM conference in Cleveland, USA in 1984. Since then, he has attended all but one of the conferences of the International Society on MCDM. He organized the 15th International MCDM conference in Ankara, Turkey in 2000. He has been a member of the Executive Committee and the chair of the Awards Committee of the International Society on MCDM for many years. He is the founding president of the INFORMS Section on MCDM. Murat enjoys working with graduate students. He has supervised many M.Sc. theses and Ph.D. dissertations. The dissertations he supervised on MCDM are those of Paul Sagala, Esra Karasakal, Selcen Phelps, Banu Soylu, Özgür Özpeynirci, and Emre Balıbek. Murat has a passion for tennis and downhill skiing. He takes every opportunity to do both. Murat is married to Suna and they have a son, Barış. Barış is a sophomore at Duke University, thinking of majoring in Decision Science. Pekka Korhonen was born in Kuopio, Finland, November 26, 1944. Finland had just come out of the war and the country was poor. Pekka was perhaps the only one of his childhood friends who entered high school. After graduating from high school, Pekka studied mathematics at Helsinki University. Mathematics was a very popular subject at the time. Pekka completed his B.Sc. and M.Sc. degrees in the late 1960s. Then he worked for a decade at the Helsinki University Computer Centre, honing his

Pekka Korhonen

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computer skills. After meeting Jyrki Wallenius in 1974 at a Mathematical Programming Conference in Eger, Hungary, he became interested in graduate studies in computational statistics, which he rapidly finished (in 1977) with a dissertation entitled “A Stepwise Procedure for Multivariate Clustering.” Pekka and Jyrki began to collaborate on MCDM and group decision problems in 1978, when both were spending a year at the Vaasa School of Economics, in Finland. Their exceptional collaboration has lasted for more than 30 years, although they were in different universities and different countries for much of this period. Email came to the rescue. They recalled an interesting incident in November 1985. Pekka and Jyrki were asked by the State Computer Centre to be test subjects to try the overseas email connection via a newly established BITNET node in Helsinki, while Jyrki was in Arizona, starting the email era for Finnish scholars. Pekka Korhonen has produced a creative stream of research, encompassing interactive procedures, including the Korhonen-Laakso reference direction approach and the Pareto Race (with Jyrki), various decision support tools, and behavioral decision research. He has always been keen to apply his work to solving practical problems. With a Ph.D. student, for example, he developed an approach to evaluate the efficiency of electricity distribution companies in Finland. Over the last decade Pekka Korhonen has been a prolific contributor to data envelopment analysis, in particular the interface between MCDM and DEA. Pekka Korhonen joined the faculty of the Helsinki School of Economics (HSE) in 1979 and was appointed Professor of Statistics in 1988. He is currently Professor and Ph.D. Program Director at HSE (recently renamed as Aalto School of Economics). Pekka Korhonen served as President of the International Society on Multiple Criteria Decision Making from 1996 to 2000. He received the Society’s Cantor Award in 1994. Another recognition was the choice of the KorhonenLaakso article in 1986 as one among the 30 most influential papers published by the European Journal of Operational Research over its 30year history. The Finnish Operations Researcjh Society appointed Pekka Korhonen its Honorary President. Pekka Korhonen also has awards and recognitions related to his early software development.

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Pekka spent a year at the University of Georgia, hosted by Ralph E. Steuer. He also served as Project Leader of the Decision Analysis and Support (DAS) Project at IIASA during 1997–1998. Pekka is married to Kaiju. They have seven children, nine grand children and three dogs. Pekka enjoys target shooting, badminton, mushroom picking, and their home Villa Havina in Huhmari (near Helsinki). Oleg Ivanovich Larichev (1934–2003) was born in Brjansk, in Central Russia, September 20, 1934. He graduated from the Department of Automation and Remote Control of the N.E. Bauman Moscow State Technical University, with an M.Sc. degree in Mechanical Engineering in 1958. He received his Ph.D. in Technical Cybernetics (a field which was not uncommon in the USSR), from the Institute of Control Problems of the USSR Academy of Sciences, Moscow, in 1965. Beginning in Oleg Larichev 1976 he was affiliated with the Institute for Systems Studies of the USSR Academy of Sciences (VNIISI), Moscow (currently the Institute for Systems Analysis of the Russian Academy of Sciences, ISA), where he was a department head from 1980, and for several years, a colleague of Leonid Kantorovich, the only Soviet Nobel Laureate in Economics, who is credited with developing linear programming. Over the last 40 years, Oleg Larichev’s research was related to multiple criteria decision making, artificial intelligence, and the psychology of decision making. He was the author of several books and more than 200 articles both in Russian and in English. His early studies dealt with control theory and its applications. During the latter part of the 1960s, Oleg Larichev began his research in MCDM. One of the first interactive multicriteria decision techniques named the STEP-Method (STEM) was developed by Oleg Larichev together with French colleagues in 1971. During the 1980s and 1990s, Oleg Larichev, together with his colleagues,

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developed a number of new decision support methods. His research in some sense culminated in the verbal decision analysis, where a model’s inputs are expressed in a natural language. Oleg Larichev served as a consultant and expert for the USSR Academy of Sciences, the USSR State Committee for Science and Technology, the USSR State Planning Committee, and different governmental agencies and companies. In 1990 Oleg Larichev was elected a Corresponding Member of the USSR Academy of Sciences, and in 1997 a Full Member of the Russian Academy of Sciences. In fact, he was the only academician in our field. Furthermore, he received the Order of “Friendship” of the Russian Federation as well as medals “In Memory of the 850th Anniversary of the City of Moscow” and “Veteran of Labor.” In 1994 Oleg Larichev was awarded the Gold Medal of the International Society on Multiple Criteria Decision Making. Many of us appreciated Oleg’s gentlemanly qualities. He was a good friend to many. He was an active participant in many international conferences and workshops. According to his old friend Rex Brown, “during the confrontation between the Red Army and the Russian Parliament led by Yeltsin, Oleg was out of town, but he was proud of his gutsy wife, Emma, who joined arms with other Yeltsin supporters and faced down the opposing tanks until they slunk away.” Oleg enjoyed classical music and art. Alexander Lotov was born in Moscow, April 12, 1946. He was educated in mathematics and computational science in Moscow. He received an M.Sc. in Dynamic Systems Control from the Moscow Institute for Physics and Technology in 1969 and a Ph.D. in Computational Mathematics (with applications to planning problems) from the Computing Centre of the USSR Academy of Sciences in 1973. In 1986 he did his “habilitation” on new visual computer-based decision support tools. Lotov is Chief

Alexander Lotov

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Researcher and Head of the Department of Mathematical Methods for Economic Decision Analysis, at the Dorodnicyn Computing Centre of the Russian Academy of Sciences, Moscow and (part-time) Professor, Faculty for Computational Mathematics and Cybernetics, Lomonosov Moscow State University. Lotov’s research interests include multiple criteria optimization, decision support in environmental problems, human/computer interaction, graphic decision support and data analysis in computer networks, and public decision support via the Internet. Lotov’s main research results are related to methods for approximating and visualizing the Pareto frontier in case of more than two criteria. Lotov has authored or co-authored eight books and over 100 research papers on the aforementioned topics. His books include Interactive Decision Maps, Approximation and Visualization of the Pareto Frontier published by Kluwer in 2004 and the textbook with I. Pospelova, Multiobjective Decision Making, published in Russian by MAKS Press, Moscow, 2008. Lotov has collaborated extensively with researchers abroad, beginning during the Soviet period. He served as a staff member of the International Institute for Applied Systems Analysis, Laxenburg, Austria, in 1981. He has collaborated with several Finnish researchers on MCDM problems over a 20-year period, as well as with specialists in water resources management at Cornell University and the Politecnico di Milano. In addition, Lotov has consulted with the Ministry of National Infrastructures, Israel, and has been a Visiting Professor at the University of Siegen, Germany, 2000–2001. His textbook Introduction into Mathematical Modeling of Economic Systems received the Silver Medal at the USSR Exhibition of National Achievements in 1989. In 1997, he received the Governmental medal “In Memory of the 850th Anniversary of the City of Moscow.” In 2000, Lotov received the Edgeworth-Pareto Award of the International Society on Multiple Criteria Decision Making. His main hobby is music, in particular, American jazz from the 1950s and 1960s.

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Benedetto Matarazzo was born in Catania, Sicily, March 10, 1946. He received his college education at the University of Catania from 1964 to 1969. Since 1986 he has been Professor of Financial Mathematics at Dipartimento di Economia e Metodi Quantitativi, University of Catania. He was Dean of the Faculty of Economics from 1999 to 2001, and he serves as Chairman of the degree program in Corporate Finance at the same faculty. Benedetto Matarazzo has been an active participant, lecturer and organizer Benedetto Matarazzo of the MCDA Summer Schools. He organized two of them in Catania: the first in 1983 and the seventh in 2000. He has also organized and served as a member of the program committees of many international scientific conferences. For example, he was Chairman of the Program Committee of EURO XVI (Brussels, 1998). Matarazzo’s research interests include preference modeling (in particular, the rule-based approach), decision aid, and decision support in general. He has published many papers on the above mentioned topics. He has published several papers jointly with Roman Słowin´ski and Salvatore Greco on rough set theory. He received, with Greco and Słowin´ski, the Best Theoretical Paper Award, by the Decision Sciences Institute (Athens, 1999). Their paper titled “Rough Set Theory for Multicriteria Decision Analysis,” published in the European Journal of Operational Research in 2001, was selected by EJOR as one of the 30 most influential papers published by EJOR over a 30-year period. In 2009, he received the Gold Medal from the International Society on Multiple Criteria Decision Making. Benedetto — always the gentleman and perfect host, enjoys good food. He also enjoys swimming and soccer. Benedetto has first hand experience from Mount Etna erupting a few years ago, when some small towns around Catania were flooded with volcanic ash. Wojtek Michalowski was born in Warsaw, Poland, November 6, 1949. He received a Master’s degree in Economics (Econometrics) in 1972 and

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a Ph.D. in Operations Research from the Warsaw School of Economics in 1980. He was Assistant Professor at the Warsaw School of Economics from 1980 to 1983, then emigrated to Algeria (University d’Annaba) and Canada (Carleton University 1985–2000). At Carleton University, Wojtek Michalowski collaborated extensively with Gregory Kersten on negotiation research. Wojtek Michalowski is currently Professor of Decision and Management Sciences at the Telfer School of Management and the University Research Wojtek Michalowski Chair in Health Informatics and Decision Support, reflecting his interests in medical decision making. Formerly Director of the Master of Health Administration Program, he is currently also Adjunct Professor at the Faculty of Medicine, University of Ottawa, and Adjunct Research Professor at the Eric Sprott School of Business, Carleton University. Wojtek Michalowski is Principal Investigator of the MET3 Research Program working to develop a clinical decision support system for point-of-care applications. During the 1997–1998 academic year he was a senior research scholar at the International Institute for Applied Systems Analysis in Laxenburg, Austria. For several years he served as Chair of the Awards Committee of the International Society on Multiple Criteria Decision Making. With a strong background in MCDM and negotiation research, Wojtek’s research interests include health informatics, with special emphasis on decision analysis and support, design of ubiquitous and mobile support systems, data mining, and multiple criteria decision making. He has written more than 80 refereed papers and has published articles in roughly 30 journals, including Management Science, Operations Research, and the Journal of Optimization Theory and Applications. His most important MCDM publication is with T. Szapiro, “A Bi-reference Procedure for Interactive Multiple Criteria Programming,” published in Operations Research, 1992. Wojtek enjoys both tennis and downhill skiing, and he excels at both. 3

Mobile emergency triage.

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Kaisa Miettinen was born in Sulkava, Finland on July 25, 1965. She defended her doctorate at the University of Jyväskylä, Department of Mathematics, in 1994. The title of her dissertation was “On the Methodology of Multiobjective Optimization with Applications.” Kaisa Miettinen has been Professor of Industrial Optimization at the University of Jyväskylä since 2007. Prior to that, she served for four years as Professor of Financial Mathematics at the Helsinki School of Economics and received the title of Kaisa Miettinen “Researcher of the Year 2007” at the Helsinki School of Economics. In 1998, she was a visiting research scholar at IIASA, Laxenburg, Austria. Kaisa’s specialty is multiobjective optimization, in particular, nonlinear multiobjective optimization. In 1999 she published a well known book titled Nonlinear Multiobjective Optimization. Her research interests include theory, methods, software and applications of multiobjective optimization. She is the recipient of the Väisälä Award from the Finnish Academy of Science and Letters. She belongs to the editorial boards of four international peer-reviewed journals in the field of optimization. Kaisa was elected President of the International Society on Multiple Criteria Decision Making in 2008. She will succeed Jyrki Wallenius as President in 2011. She served as Secretary of the Society from 1997– 2008 and is the General Chair of the 2011 MCDM Conference, to be held in Jyväskylä, Finland, in June, 2011. She has been one of the organizers of three Dagstuhl seminars in Germany where the focus has been to bring together researchers from MCDM and evolutionary multiobjective optimization fields. Furthermore, she has been a member of the Managing Board of EUROPT, the Continuous Optimization Working Group of EURO since 2006 and the Chair of EUROPT from 2010–2012. She was the President of the Finnish Operations Research Society from 2002–2003 and has been a member or a deputy member of the board since 1997. She is also the Vice-Chair of the Finnish Society on Computational Sciences.

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Kaisa’s father invented the Sulkava Rowing Race, the world’s biggest rowing competition. Kaisa studied hard at school and liked mathematics and many other subjects from an early age. She became interested in multiobjective optimization after Professor Pekka Neittaanmäki suggested it to her as a Master’s thesis topic. Kaisa’s hobbies include baking, picking berries and mushrooms and enjoying outdoor activities. Hirotaka Nakayama was born on February 23, 1945 in Kyoto, Japan. He received his B. Eng., M. Eng., and D. Eng. degrees in 1969, 1971, and 1974, respectively, all in Applied Mathematics and Physics from Kyoto University. He is a professor in the Faculty of Intelligence and Informatics at Konan University, Japan. Hirotaka Nakayama’s research interests include multiobjective optimization, machine learning, pattern recognition, sequential approximate optimization using computaHirotaka Nakayama tional intelligence, and applications in these areas. He is particularly interested in engineering applications of multiobjective optimization. Hirotaka has published many books, chapters, and articles in the above areas. Hirotaka has served and continues to serve on the editorial boards of several journals. He has received two application awards from the Japanese Society of Operations Research as well as the Edgeworth-Pareto Award from the International Society of Multiple Criteria Decision Making in 1995. Hirotaka (together with Professor Yoshikazu Sawaragi) was a contributor to the first IIASA Volume in the International Series on Applied Systems Analysis (Conflicting Objectives in Decisions, edited by David Bell, Ralph Keeney and Howard Raiffa). Since then Hirotaka has been an active visitor to IIASA and an active contributor to IIASA activities. Hirotaka enjoys gardening. Howard Raiffa was born in 1924 in New York City. When Howard was seven, the Raiffa family moved to a four-room apartment in the

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Bronx that overlooked the school yard where he spent many daylight hours playing sports. From about the age of 12, he found his passion in basketball and played it incessantly. He chose to attend a huge high school with an outstanding basketball team. In his senior year he became captain of the team. His family always wanted their children to do well in school, even though the family was not academically-oriented in any way. Raiffa entered the (free) City College of New York (CCNY) primarily to take mathematics Howard Raiffa courses. Although he excelled in mathematics, he was a B student otherwise. He entered the army during his sophomore year at CCNY. After several years in the Air Force, much of it spent in Japan, he completed his military service and then entered the University of Michigan to study actuarial science. Because of his prior coursework, he was able to complete his degree in a very short time. He entered the statistics program and completed his Master’s degree in one year (1946). He then pursued his Ph.D. in Mathematics at Michigan. He became interested in game theory and wrote a report on it for a research grant that helped to support him while he was doing his degree. Prior to his oral exam, members of the faculty read the report he had written. They were sufficiently impressed with his work that they decided he need not do an oral exam. Furthermore they accepted his report as his doctoral dissertation! He completed his degree in 1951, with his dissertation work providing seminal research in game theory. Because of his surprise and how late in the academic year he discovered that he had completed his degree requirements, he took a one-year postdoctoral position in a joint program in mathematics and psychology at the University of Michigan. The next year (1952) Raiffa joined the Department of Mathematical Statistics at Columbia University as a faculty member, where he remained for five years. While there he wrote a book (with Duncan Luce) titled Games and Decisions. Harvard hired him in 1957. He is currently the

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Frank P. Ramsey Professor (Emeritus) of Managerial Economics, a joint chair held in the Business School and the Kennedy School of Government at Harvard University. Raiffa is an originator of the famous “decision tree.” He has done extensive research on developing techniques to help decision makers think more systematically about complex choices involving uncertainties and trade-offs. He has also worked actively in negotiation theory. As an advisor to McGeorge Bundy, White House Assistant for National Security under Presidents Kennedy and Johnson, Raiffa helped negotiate the creation of an East-West think tank aimed at reducing Cold War tensions. The think tank was named the International Institute for Applied Systems Analysis (IIASA) and is located in Laxenburg, Austria. Raiffa became the Institute’s first director and served in that capacity from 1972 to 1975. He was also one of four founders of the Kennedy School at Harvard and a cofounder of the Negotiation Program at the Harvard Law School. He retired from the active faculty in December 1994. Howard Raiffa has received many awards, including several honorary doctorates (from Carnegie Mellon, Harvard, the University of Michigan, Northwestern University, and Ben-Gurion University of the Negev). He is also a recipient of the Gold Medal from the International Society on Multiple Criteria Decision Making. He and Ralph Keeney received the 2002 INFORMS Expository Writing Award for their publications in operations research and the management sciences that have set an exemplary standard of exposition. In addition Raiffa was elected to the American Academy of Sciences and the National Academy of Engineering. Raiffa advised approximately ninety Ph.D. students during his academic career. Raiffa is author or co-author of many publications including several classic books. These include Decisions with Multiple Objectives: Preferences and Value Tradeoffs published in 1976 (with Ralph Keeney), a three-author book (Hammond, Keeney and Raiffa), Smart Choices: A Practical Guide to Making Better Decisions, 1998, and Negotiation Analysis: The Science and Art of Collaborative Decision Making (published with others, 2007).

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Carlos Romero was born on October 14, 1946 in the district of Chamberi (Madrid), Spain. He received a B.Sc. degree in Agricultural Science from the Polytechnic Institute of Madrid in 1967. Carlos obtained his M.Sc. and Ph.D. degrees in Agricultural Economics from the Technical University of Madrid in 1970 and 1972, respectively. His Ph.D. dissertation was supervised by Professor Enrique Ballestero. He also received a second M.Sc. degree in Statistics and Operational Research from Universidad Complutense, Carlos Romero Madrid, in 1973. Carlos is Professor of Economics as well as the head of the research group “Economics for a Sustainable Environment” at the Technical University of Madrid. He is well known for his contributions to goal programming. He has widely used multiple criteria decision methods in various application areas, especially in the field of environmental economics and natural resources management. He was awarded the National Prize in Economics and the Environment from the Spanish Ministry of Environment in 2001 and the Georg Cantor Award from the International Society on Multiple Criteria Decision Making in 2006. Carlos enjoys painting, literature and sports. He especially likes the Spanish painter Goya and the Russian writer Dostoyevsky. He is an avid jogger and has jogged over 40,000 kilometers in and around major cities of the world. He currently lives in his beloved Chamberi with his only son, his nephew-in-law and his cat, all avid supporters of the Real Madrid soccer team (cat included). Bernard Roy was born on March 15, 1934 in France. He started losing his sight at an early age, and his reading and writing deteriorated over the years. During secondary school, he started using a mechanical typewriter to take notes. Despite his vision problems he was an outstanding student. He received his Licence degree from the Université de Paris in 1954. He graduated from the Institute of Statistics of the Université Paris (ISUP) in 1957 with a Masters degree. Bernard received his Ph.D. in Mathematics

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from Université Paris in 1961. His dissertation was on graph theory and its applications (in particular, activity-on-node formulations to project scheduling); it was supervised by Claude Berge. Bernard had a good friend, Patrice Bertier — a fellow student in mathematics — who contracted poliomyelitis during his youth and was confined to a wheel chair. Patrice persuaded Bernard to enroll in the l’Institut d’Etudes Politiques (IEP — a special Grande École mainly oriented towards Bernard Roy economics and political science) in October 1954, in addition to enrolling in ISUP. It was extremely uncommon for someone holding only a mathematics degree to enroll in IEP. Patrice and Bernard were, for this reason, viewed as a very strange couple. This strangeness was reinforced by the fact that Bernard, half blind, guided by Patrice, had to push his wheel chair from one institute to the other (one and a half miles apart on Boulevard Saint Germain and Boulevard Saint Michel). After successfully completing the mid-term exams, they learned that the final exams were scheduled for the same day in both institutes and they had to make a choice. They both chose ISUP. Roy was interested in applying mathematics to real-world problems. He started applying mathematics to problems while a student. In October 1957 he joined SMA (Société de Mathématiques Appliquées), a small consulting company. They were most successful in applying OR to different problems over a short period of time. The company grew quickly and became SEMA-Metra International, with multiple branches in Europe. After working as a consultant applying operations research for many years, Bernard became a professor at the Université de Paris in 1972 and he founded a new research center, LAMSADE, shortly thereafter. He was the director of LAMSADE until 1999. He founded the EURO Working Group on Multiple Criteria Decision Aiding in 1975. He became an Emeritus Professor in 2001, but continues his research and consulting activities.

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Bernard has made important contributions to graph theory and multiple criteria decision making. He developed the concept of outranking relations to address multiple criteria problems, developed a series of ELECTRE methods, and applied them to many real life problems over the years. Bernard published extensively in these areas. Many researchers have followed and extended Bernard’s pioneering ideas and have further developed and applied outranking methods. Bernard Roy has received many awards. He was awarded honorary doctorates from seven universities. He received the EURO Gold Medal in 1992 from the Association of European Operational Research Societies and the MCDM Gold Medal in 1995 from the International Society on MCDM. In 2002, his colleagues (Bouyssou et al.) edited a volume in his honor, with the contributions of many scholars in the area of MCDM. In addition to his research, Bernard is interested in history and oenology. Thomas L. Saaty was born in 1926 (to an American parent) in Mosul, Iraq, and moved to the United States in his youth. He received his B.A. from Columbia Union College in 1948. He received an M.Sc. in Physics from the Catholic University in 1949 and an M.A. in Mathematics from Yale in 1951. He did postgraduate study at the University of Paris, and received his Ph.D. in Mathematics at Yale in 1953. Saaty worked for fifteen years for US government agencies and for companies doing government-sponsored research, Thomas Saaty including the RAND Corporation. He then taught at the Wharton School of the University of Pennsylvania from 1969–1979. He is currently a Distinguished University Professor at the Joseph M. Katz Graduate School in the University of Pittsburgh. He has made numerous contributions to the fields of operations research, including queuing theory, graph theory, behavioral mathematics, and arms control. Demonstrating the breadth of his interests, Saaty (with

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George Dantzig) is the author of Compact City, A Plan for a Liveable Urban Environment, 1973. He is the author of more than 300 papers and 30 books on mathematics, operations research, and decision making. He is the inventor, architect, and primary theoretician of the analytic hierarchy process (AHP), a widely used method of multiple criteria decision making. An extensive feature article on his AHP research and its applications appeared in Fortune magazine in May 1999. Saaty has been elected to the National Academy of Engineering and the Spanish Royal Academy of Sciences. He is the recipient of many awards, including the Gold Medal of the International Society on Multiple Criteria Decision Making and the INFORMS Impact Prize for his development of the analytic hierarchy process. He also served and continues to serve in editorial positions with multiple academic journals, and he is a member of several academic and other societies. Tom Saaty is also a collector, editor, and publisher of 21 books on “The Thinking Man’s Humor,” under various pseudonyms. He is also a classical music fan, and owns a comprehensive collection of both books on Beethoven as well as recorded works of Beethoven. Tom is married to Rozanne, an active AHP scholar. Masatoshi Sakawa was born in Matsuyama, Japan, August 11, 1947. He received a B.E. in 1970, an M.E. in 1972, and a D.E. in 1975, all in Applied Mathematics and Physics at Kyoto University. The title of his doctoral dissertation was “Studies on Optimal Control and Multiple-Objective Optimization.” He worked at Kobe University and Iwate University, before being appointed Professor at the Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University in 1990. Masatoshi Sakawa Sakawa is a prolific writer. He has published more than 300 papers and is the author of 20 books (6 in English and 14 in Japanese), several of which deal with fuzzy sets and multiple

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objectives. One of his most popular books is Fuzzy Sets and Interactive Multiobjective Optimization, published by Plenum in 1993. His research interests include fuzzy decision making, MCDM, man-computer interaction, multiobjective games, genetic algorithms, and environmental applications. Sakawa has been an active participant in IIASA Workshops. He was on sabbatical from March to December 2009, first at IIASA, Laxenburg, Austria and then at Imperial College, London, UK. Sakawa received the Georg Cantor Award of the International Society on Multiple Criteria Decision Making in 2002. Sakawa enjoys classical music. Yong Shi was born on August 24, 1956 in Chengdu, China. He obtained his B.Sc. degree in Mathematics from Southwest Petroleum Institute, Sichuan, China in 1982 and received his MBA from the National Center for Industrial Science and Technology Management Development, Dalian University of Science and Technology, China in 1983. He wrote his dissertation under the supervision of Professor Po-Lung Yu and obtained his Ph.D. degree in Management Science from the University of Kansas in Yong Shi 1991. Yong Shi currently holds several positions. He is the Charles W. and Margre H. Durham Distinguished Professor of Information Technology, College of Information Science and Technology at the University of Nebraska at Omaha. He is Executive Deputy Director at the Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences and the Associate Dean at the School of Management, Graduate University of the Chinese Academy of Sciences, Beijing. Yong’s research interests include multiple criteria decision making, data mining and their applications. He has published many books and articles. He is the founder and Editor-in-Chief of the International Journal of

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Information Technology and Decision Making and has held other editorial responsibilities for other journals. He organized numerous conferences and served as the co-chair of the 20th International Conference on MCDM held in Chengdu, China. Yong has received many awards for his scholarly work including the Georg Cantor Award from the International Society of MCDM in 2009. Yong is married to Bailing Gong who has been most supportive of his research activities in MCDM and has accompanied him to MCDM Conferences. Their son, Chris Shi, is currently a Ph.D. student in the Astrobiology Program at the University of California at Los Angeles (UCLA). Yong is an avid swimmer. He tries to swim every day. He loves reading and enjoys classical music. Roman Słłowińński was born March 16, 1952 in Poznań, Poland. He earned his Ph.D. in 1977 in Computer Science from the Poznań University of Technology and Dr. Habil. in Decision Sciences, also from Poznań University of Technology in 1981. Since 1989, Roman Słowiński has been Professor and Founding Head of the Laboratory of Intelligent Decision Support Systems within the Institute of Computing Science, Poznan´ University of Technology, Poland. He also holds a Professor’s posiRoman Słłowin´ski tion, beginning in 2002, at the Systems Research Institute of the Polish Academy of Sciences in Warsaw. He has been European Chair Professor at the Université de Paris Dauphine, Visiting Professor at the Swiss Federal Institute of Technology in Lausanne and at the University of Catania. He is fluent in French, and translated Bernard Roy’s book Méthodologie Multicritère d’Aide à la Décision into Polish. Roman Słowiński has conducted research on the methodology and techniques of decision aiding, including multiple criteria decision making, preference modeling, modeling of uncertainty in decision problems, and knowledge-based decision support. This

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methodology cleverly combines operations research and computational intelligence. Roman Słowiński is perhaps best known for his seminal work on using rough sets in decision analysis. He started this work with the founder of the rough set concept, the late Zdzisław Pawlak in 1983, and continued with Salvatore Greco and Benedetto Matarazzo beginning in the 1990s. He organized the First International Workshop on Rough Set Theory and Applications in Poznań, in 1992. His publications include 14 monographs and over 350 scientific articles in international journals and edited volumes. He has supervised 23 Ph.D. theses in operations research and computer science. Roman Słowiński is also the Editor-in-Chief of the European Journal of Operational Research (EJOR), a most important outlet for MCDM research, since 1999. He is recipient of the EURO Gold Medal (1991) and the EdgeworthPareto Award of the International Society on Multiple Criteria Decision Making (1997). In 2004, he was elected as a member of the Polish Academy of Sciences, an institution of 350 outstanding Polish scholars. In 2005, he received the Annual Prize of the Foundation for Polish Science. Additional recognitions include Doctor Honoris Causa of Polytechnic Faculty of Mons (2000), University of Paris Dauphine (2001) and Technical University of Crete (2008). Roman is married to Teresa. Teresa has been, since 1999, assisting him with the European Journal of Operational Research. They have four children. Their oldest son Jan graduated from the Faculty of Theology of the Pontifical Lateran University (Lateranum) in Rome and was ordained a Catholic priest in 2002. In 2008 he obtained a Ph.D. in Canon Law from the Pontifical Lateran University. Presently, he is completing a three-year study at the Sacred Roman Rota (Sacra Rota Romana) in the Vatican. Roman enjoys photography and wine tasting. Jaap (Jacob) Spronk was born in Rotterdam, the Netherlands, August 7, 1949, on an exceptionally sunny day, at least in the Netherlands. Jaap Spronk received his undergraduate degree from Erasmus University. His M.Sc. degree in Econometrics was awarded by the Netherlands Institute of Econometrics. Jaap returned to Erasmus University to com-

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plete his Ph.D. degree. His advisors were Peter Nijkamp and Aart Diepenhorst. Jaap Spronk is the Academic Dean of MBA Programs for the Rotterdam School of Management (RSM), Erasmus University. He is also the Academic Director of the MFM Program and a Professor of Financial Management Science. As a member of the Faculty of Economics at Erasmus University, Spronk has been a Full Professor of Finance since 1982. He served as Vice-Dean of InterJaap Spronk national New Business Development from 2003 to 2008; Director of Studies for the Faculty of Economics from 2003 to 2007; Director, Division of Accounting and Finance from 1996 to 2003; and Chair of the Department of Finance from 1984 to 2003. He has initiated several important programs for the RSM, including an M.Sc. and a one-year Specialized Executive Master’s degree in Financial Management. He is the co-creator and Academic Director of the XIFM, the Executive Master’s in Islamic Financial Management, which reflects one of his current research interests. Jaap is a polyglot. He is fluent in Dutch, English, French, German and Italian. Jaap Spronk has been a professor at a number of foreign universities, including Bocconi, and has held Visiting Professorships at the Helsinki School of Economics, the Universita di Bergamo, and the State University of New York at Buffalo. He has been a Fellow of the European Institute for Advanced Studies in Management in Brussels, as well as at ERIM, Research Programme Accounting and Finance, and is a member of numerous advisory boards for global financial institutions. Jaap was President of EURO, the Association of European Operational Research Societies (1991–1992). He is a frequently invited lecturer for universities and conferences around the world and has chaired numerous selection committees for professorships in Europe and the United States. Beyond his life in academia, Professor Spronk is often called upon as a consultant for government and industry organizations, banks and institutional investors.

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Jaap Spronk’s current research interests include financial management science, performance evaluation, multidimensional finance, and Islamic finance. Jaap Spronk is the recipient of numerous awards, including the Gold Medal of the International Society on Multiple Criteria Decision Making (2002), the Umbra Erasmi Medal of Erasmus University (1996), and the Gold Medal of the University of Crete, Greece (1996). He has been a member of the Royal Dutch Society of Sciences (Hollandse Maatschappij der Wetenschappen), since 1988. Jaap is married to Yvonne. They have two children: Sarah and Thomas, and one granddaughter: Carmen. Jaap likes all people and therefore enjoys working at the Rotterdam School of Management. Ralph E. Steuer was born in New York City, September 15, 1940. At the age of two, the family moved to Rahway, NJ, just outside New York City. Ralph’s father, who was born in Germany, worked for a firm that made precision parts for the plastics industry. Ralph’s mother, although born in the US, spent a number of childhood years in Germany, Argentina, Uruguay and Brazil, and this led her to become a high school teacher of Spanish and German. Ralph’s parents loved to travel and took the family on many trips. Ralph Steuer From 8th grade on, if anyone asked Ralph where he was going to college, his answer was Brown University. This was the result of being dragged from college to college so that his sister, who is four years older, could make her selection. While she ultimately chose another university, Ralph knew from the minute he saw Brown University that it was for him. In high school Ralph was on the track team for three years and the swimming team for two. His performance on the two teams was completely opposite. On the track team Ralph was defeated only once in three years in the one-mile run. But on the swimming team, he came in last every time except once, and that was when one of the

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swimmers on the other team got a mouthful of water. He also ran at Brown and became captain of the cross country team in his senior year. After graduating with a degree in Electrical Engineering, Ralph took a job with Westinghouse in Pittsburgh, PA, but left after 14 months to pursue an MBA in Accounting and Finance at Cornell University, graduating in 1964. Then after working for two years in Chicago, he enrolled in the Ph.D. program in Quantitative Methods in Business at the University of North Carolina in 1968. There he had the good fortune to work with Professor John P. Evans, who gave him the dissertation topic of vector maximization. His ADBASE code for multiple objective linear programming was included in an appendix to his dissertation. Ralph’s first academic job was at the University of Kentucky. It was from there that he attended the MCDM conference organized by Milan Zeleny at the University of South Carolina in 1972. Then there was the Jouy-en-Josas conference in 1975 and the many other international MCDM activities that followed which have come to characterize the field. Ralph was at the University of Kentucky from 1972 until 1981, except from 1978–1979, during which he was at Princeton. The year at Princeton was one of his most productive years. He began his book there and was able to “join forces” with Jonathan Kornbluth who was visiting Wharton (48 miles away) at that time for several papers; he also got involved in some water resources research with Princeton colleague Eric Wood. In 1981 he joined the management science department in the University of Georgia and worked under Roscoe Davis (the world’s greatest boss). With the university giving him great support along with others such as Jaap Spronk, Jared Cohon, Yong Shi, and Stan Zionts, he was able to publish MCDM WorldScan until it became impractical because of the Internet and sky-rocketing postal costs. In his first fifteen years at the University of Georgia he had many visitors, for example, Manfred Grauer, Iwan Stanchev, Pekka Korhonen, Dagmar Glückaufova, Igor Perehkod, Alexander Lotov, Alexander Topchisvili, Tadeusz Trzaskalik, Heinz Isermann, Tomas Gal, Birsen Karpak, Geoff Lockett, Francisco Ruiz, and many others, with most staying at his home during their visit. In 1999 the management science department at the University of Georgia was

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dissolved and Ralph moved to the finance department where he has found a home doing multiple criteria portfolio selection and related MCDM topics. Ralph lives with his wife Judy in Athens, GA; the couple has two daughters, both of whom live in Atlanta. Theodor (Theo) J. Stewart was born in Cape Town, South Africa, September 16, 1943. Theo Stewart’s (first) B.Sc. was in Chemical Engineering at the University of Cape Town. He then worked as a chemical engineer (1964–1971) and continued parttime studies in Operations Research and Statistics through the University of South Africa, the largest distance education university in South Africa. Stewart completed his second B.Sc. in 1972, an M.Sc. (OR) the following year, and a Ph.D. in Mathematical Theodor J. Stewart Statistics (with a thesis entitled “Bayes Optimal Experimental Design for Determination of a Response Surface Maximum”) in 1976. Theo Stewart retired at the end of 2008 from the University of Cape Town, South Africa, having been Professor there since 1984, including a period as Department Head in the 1990s. He has recently been appointed part-time Professor at Manchester University, to be closer to his two children who reside in the UK. Theo Stewart is primarily an operational researcher, and his particular areas of interest are multi-criteria decision analysis, multiobjective mathematical programming, Bayesian statistics, and applications of these methods in resource management and industrial planning, in particular fisheries and water resources management. Theo Stewart co-authored with Valerie Belton (University of Strathclyde, Glasgow), a book on Multiple Criteria Decision Making: An Integrated Approach (published by Kluwer Academic Publishers in 2002). In total, Stewart has authored or co-authored some 80 papers. One of the better known is his paper with Vahid Lotfi and Stanley Zionts: “An Aspiration-Level Interactive Model for Multiple Criteria Decision

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Making,” Computers and Operations Research, 1992, which describes a simple, eclectic approach for solving discrete alternative multiple criteria decision problems. Theo Stewart’s leadership was sought in several instances. He served as Vice President of International Federation of Operational Research Societies (IFORS) from 2004 to 2006, and President of the International Society on Multiple Criteria Decision Making from 2004 to 2008. He is the new Editor-in-Chief of the Journal of Multi-Criteria Decision Analysis (2009) and plans to restructure the journal. In 2008 he was awarded the Gold Medal of the International Society on Multiple Criteria Decision Making. He has also been awarded the Operations Research Society of South Africa’s Tom Roszwadowski Medal for written contributions to operations research five times. Theo Stewart hosted the 1997 International Conference on Multiple Criteria Decision Making in Cape Town. This was for many participants their first visit to this beautiful country. Theo enjoys a glass of good wine and visits to vineyards in the Western Cape region. Gwo-Hshiung Tzeng was born in Taiwan in 1943. He received his Bachelor’s degree in Business Management from Tatung Institute of Technology, Taiwan in 1967, his Master’s degree in Urban Planning from Chung Hsing University, Taiwan in 1971, and his Ph.D. in Management Science from Osaka University, Japan in 1977. Gwo-Hshiung is a Chaired Professor at Taiwan’s National Chiao Tung University. He worked as a research associate at the US Department of Energy’s Argonne National Gwo-Hshiung Tzeng Laboratory and as a visiting professor at the Department of Civil Engineering at the University of Maryland, College Park. He was also a visiting scholar at Stanford University’s Department of Management Science and Engineering, Energy Modeling Forum.

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Gwo-Hshiung was named a National Distinguished Chaired Professor, the highest honor offered by Taiwan’s Ministry of Education, as well as a Distinguished Research Fellow, the highest honor offered by Taiwan’s National Science Council. He received the MCDM EdgeworthPareto Award from the International Society on MCDM in 2009. His joint paper with Serafim Opricovic (“Compromise Solution by MCDM Methods: A Comparative Analysis of VIKOR and TOPSIS,” EJOR, 2004) was identified by Thomson Reuters’ Essential Science Indicators (ESI) as one of the most cited papers in the field of economics in 2009. His current research interests include statistics, multivariate analysis, networks, routing and scheduling, multiple criteria decision making, fuzzy set theory, hierarchical structure analysis with application to technology management, energy, environment, transportation systems, transportation investments, logistics, location, urban planning, tourism, technology management, electronic commerce, and global supply chains. Gwo-Hshiung Tzeng founded the Taiwan affiliate chapter of the International Association of Energy Economics in 1984. He was Chairman of the 10th International Conference on Multiple Criteria Decision Making in 1992, Co-Chairman of the 36th International Conference on Computers and Industrial Engineering in 2006, and Chairman of the International Summer School on Multiple Criteria Decision Making in 2006. He is currently the Editor-in-Chief of the International Journal of Operations Research and International Journal of Information Systems for Logistics and Management.

Philippe Vincke

Philippe Vincke was born on April 30, 1951. He received all his degrees from the Université Libre de Bruxelles (ULB). He received a Master’s degree in Mathematics in 1973 and a second Master’s degree in Actuarial Science in 1977. He obtained his Ph.D. in Mathematics in 1976. Philippe is currently Rector of ULB where he holds a professorial position. He teaches in the Faculties of Applied Sciences, Sciences, the Business School, and the Institute for Environmental Studies. He is

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also the Director of the Management Mathematics Team within the Computer and Decision Engineering Department. Philippe also served as the Dean of the Faculty of Applied Sciences and, previously, as the Vice Rector of ULB for Research and International Relations. Philippe has been an active contributor and leader of the professional community. He has served as the President of the European Association of Operational Research Societies, the Vice President of the International Federation of Operational Research Societies, and the President of the International Committee of Summer Schools on Multiple Criteria Decision Making. Philippe’s research interests include multiple criteria decision making and preference modeling. His research led to important developments in the area of outranking relations. He is the author or coauthor of six books and many journal articles. He received the Georg Cantor Award from the International Society on Multiple Criteria Decision Making in 2000 in recognition of his contributions to the field. In 2009, he received the title of Doctor Honoris Causa from the Université Paris Dauphine. Philippe is married and has two children who are 21 and 24 years old. He lives in the open country and likes tinkering, gardening, and cooking. Jyrki Wallenius was born in Kuusankoski, Finland, October 11, 1949. The Wallenius family is known among genealogists for its many (some 130) Lutheran ministers, dating back to the 1500s. His family also includes several professors. Martin Wallenius (1731– 1773) was Professor of Mathematics at Turku Academy from 1758–1773. Martin is credited for “importing” differential and integral calculus to Finland. Jyrki’s father, Jukka Wallenius, who was a mathematician by education, had a distinguished career in the Jyrki Wallenius service of the Finnish government. To satisfy his curiosity, while working at the Finnish railroads, he conducted a pioneering application of linear programming to problems in the

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Finnish railroads in 1957. Jyrki was four years old when he moved with his parents to Helsinki, where he obtained his schooling. Jyrki was always an outstanding student. Sports were important extra-curricular activities. Jyrki earned his B.Sc. (1970), M.Sc. (1971), and Ph.D. (1975) degrees from the Helsinki School of Economics (HSE). Because he was engaged at the time, Jyrki was reluctant to go to the US for a Ph.D., as suggested by a former Rector of the HSE. Instead, Jyrki became a Ph.D. student at the European Institute for Advanced Studies in Management (EIASM), Brussels, from 1972 to 1975. EIASM had been started in 1971 to help strengthen doctoral education in management in Europe. Only a small number of students who were at the institute actually lived in Brussels; many came and stayed for short periods. During the three year period, Jyrki made ten visits to Brussels, ranging from a few days to eight months. His time at EIASM was an important part of his life. It was there that he met Stanley Zionts, who supervised his dissertation from 1973–1975.4 The title of his doctoral dissertation was “Interactive Multiple Criteria Decision Methods: An Investigation and an Approach.” Stan Zionts and Jyrki Wallenius embarked on a stream of joint research that continued for over 30 years. They were often joined in their efforts by Pekka Korhonen, Jyrki Wallenius’ long-time friend and colleague. Many of Jyrki Wallenius’ (joint) contributions are seminal, in particular, the early work on interactive procedures for solving multiple objective problems, their testing, and applications. During the 1990s at the Helsinki School of Economics he branched out to behavioral decision research, computer-based decision support systems, negotiation science and later to multi-unit auctions, including combinatorial auctions. In recent years he has been actively building bridges between the MCDM and EMO communities (with Kalyanmoy Deb, Pekka Korhonen, Kaisa Miettinen and others) by suggesting novel hybrid approaches. Wallenius has always been fascinated by behavioral decision research. In fact he 4

Professor Bertil Näslund (Stockholm School of Economics) was a faculty member at the EIASM from 1971 to 1973. He was instrumental in suggesting the topic “Interactive Programming” to Jyrki Wallenius as a subject for his dissertation research in the summer of 1972. Näslund chaired the Nobel Committee for Economics during the 1990s.

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currently teaches a Ph.D. class on behavioral decision making at the HSE. Wallenius has had a very international career. He has taught or conducted research in Finland, Sweden, Belgium, Germany, France, United States, and Turkey. He has spent numerous sabbaticals in the United States, at Purdue, Texas A&M and Arizona State University. Wallenius has served many national and international scientific organizations in leadership roles. He is currently Professor and Dean of Aalto School of Economics. He served as Vice Rector of the HSE from 1999 to 2004 and as Director of the HSE International MBA Program from 1998 to 2005. He also served as an editor for the European Journal of Operational Research from 1999 to 2005 (together with Roman Słowin´ ski and Jacques Teghem). Jyrki Wallenius was elected President of the International Society on Multiple Criteria Decision Making in 2004. He received the Society’s Edgeworth-Pareto Award in 1994, the Bronze Medal of the Helsinki School of Economics in 1999, and the Jaakko Honko Medal from the Yrjö Jahnsson Foundation in 2005. Jyrki is an avid reader of biographies. He also enjoys a good game of tennis and travelling. Jyrki is married to Hannele, also an active MCDM scholar, Professor and Department Head at the Helsinki University of Technology. Over the years they have collaborated extensively on various research. Their daughter, Johanna, completed her doctorate in Economics at Arizona State University in 2010. She joined the Stockholm School of Economics, Stockholm, Sweden as a faculty member in the fall of 2010. She has attended 12 MCDM Conferences as an accompanying person, and expects to attend many more! Many remember her from Mons, when she was less than one year old. Andrzej Piotr Wierzbicki was born in Warsaw, June 29, 1937. He graduated in 1960 with an M.E. (Telecommunications and Control Engineering) and in 1964 with a Ph.D. (“Nonlinear Dynamics in Control”) from the Warsaw University of Technology (WUT). Wierzbicki did his “habilitation” in 1968 (Optimization and Decision Science) and was appointed Professor at Warsaw University of Technology in 1976. Before being employed by IIASA, he served as Dean of the Faculty of Electronics, Warsaw University of Technology. From 1979 to 1984 Wierzbicki was the

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Leader of the Systems and Decision Sciences Program of the International Institute for Applied Systems Analysis in Laxenburg, Austria. During these years IIASA served as a focal point for many MCDM activities. Many workshops were organized either at IIASA or in Eastern Europe. From 1991 to 1994 Wierzbicki served as a member of the State Committee for Scientific Research of Poland and the chairman of the Polish Commission on Applied Research. From 1996 to 2004 he was the Director General of the National Andrzej Piotr Wierzbicki Institute of Telecommunications in Poland. From 2004 to 2007 Wierzbicki served as Research Professor at the Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan. In addition to teaching and lecturing for over 45 years and supervising 20 doctoral dissertations at WUT, Wierzbicki is the author of over 200 publications, including 14 books (7 monographs, 7 edited volumes), more than 80 articles in scientific journals, over 100 papers at conferences and the author of three patents. Wierzbicki is widely known for developing the achievement scalarizing function in 1980. Its use is commonplace in various MCDM approaches today. Furthermore, Wierzbicki is the author of Creative Space: Models of Creative Processes, a recent book discussing knowledge creation, with Yoshiteru Nakamori. His current research interests are broad. They include vector optimization, MCDM and game theoretic approaches, parallelization of optimization algorithms, diverse aspects of negotiation and decision support, diverse issues important to the information society, theory of intuition, and theories of knowledge creation and management, among others. Wierzbicki has received many scientific and other awards, including the Belgian Royal Officer Cross Le Merite de l’Invention. He was the recipient of the Cantor Award of the International Society on Multiple Criteria Decision Making in 1992. Besides Polish, he speaks German, Russian, and English. Detlof von Winterfeldt was born in Duisburg, Germany, June 13, 1948. Detlof von Winterfeldt received his B.Sc. and M.Sc. degrees at the

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University of Hamburg, Germany, in 1969 and 1971, respectively, and his Ph.D. from the University of Michigan, Ann Arbor, in 1976. At the University of Michigan, he studied under Ward Edwards and majored in Mathematical Psychology. Detlof von Winterfeldt is Professor of Industrial and Systems Engineering in the Viterbi School of Engineering and Professor of Public Policy and Management in the School of Policy, Planning, and Development at the University of Southern California (USC). He was also Detlof von Winterfeldt the Director of the National Center for Risk and Economic Analysis of Terrorism Events (CREATE), a Center of Excellence funded by the Department of Homeland Security, from 2004 to 2008. Detlof von Winterfeldt served as a research scholar at IIASA during the latter part of the 1970s. He returned to IIASA as its Director in January 2009, following in the footsteps of Howard Raiffa and others. For the past thirty years, Detlof has been active in teaching, research, university administration, and consulting. His research interests are in the foundation and practice of decision and risk analysis as applied to the areas of technology development, environmental risks, natural hazards and terrorism. He has co-authored two books, two edited volumes, and is the author or co-author of over 100 journal articles and book chapters dealing with the above-mentioned topics. Detlof is particularly known for many of his interesting applications. Among others, he has co-authored several papers with Ralph Keeney and Ward Edwards. His book with Ward Edwards: Decision Analysis and Behavioral Research, published by Cambridge University Press in 1986 has been very influential. Detlof has a wide experience in consulting. As a consultant he has applied decision and risk analysis to many problems in government and the private sector. He has served on several committees and panels of the National Science Foundation and the National Academies (NAS). He is a fellow of the Institute for Operations Research and the Management Sciences (INFORMS) and of the Society for Risk Analysis. In 2000, he received the Ramsey Medal for his contributions to decision

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analysis from the Decision Analysis Society of INFORMS. In 2009, he received the Gold Medal from the International Society on Multiple Criteria Decision Making. Po-Lung Yu was born in 1940 and raised in Taiwan, Republic of China. Po-Lung learned, practiced, and mastered martial arts in junior high school. He founded the KU Kung Fu Club at the University of Kansas in 1977 for teaching Tai Chee Chuan and a variety of martial arts. He was a Master Instructor and faculty adviser of the club from 1977 to 2004. He earned his B.A. in International Trade in 1963 from the National Taiwan University. He then went to the US where he completed Po-Lung Yu his Ph.D. in Operations Research and Industrial Engineering at the Johns Hopkins University in 1969. Po-Lung Yu taught at the University of Rochester from 1969 to 1973, and then at the University of Texas at Austin from 1973 to 1977. From 1977 to 2004, he held an endowed Chair as the Carl A. Scupin Distinguished Professor of the University of Kansas, where he currently holds the position of Distinguished Professor Emeritus. He is also Distinguished Professor at the National Chiao-Tung University, Taiwan. Po-Lung Yu has received awards for research and teaching. He was a recipient of the Edgeworth-Pareto Award from the International Society on Multiple Criteria Decision Making. In addition he co-chaired with Prof. G.H. Tzeng, the 12th International Conference on Multiple Criteria Decision, Taipei, Taiwan in 1992. Over the last three decades, Yu’s research interests and activities have evolved and expanded. He started working on differential games with Dr. Rufus Isaacs (the inventor) and then worked on problems of multiple criteria. Dissatisfied with the limitations of optimization theory, game theory, and traditional decision analysis, he began to actively study human psychology and neuron science during the 1970s to explore the “root” of human decision making.

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Utilizing the findings from psychology, brain physiology, dynamic optimization systems, both eastern and western thought, and empirical observations, he built a basic model of human behavior (a dynamic MCDM model) that he has named habitual domain theory and competence set analysis. Po-Lung Yu has published 16 books and more than 150 professional articles which can be classified into seven areas: (A) multiple criteria decision making, (B) behavior mechanisms and habitual domain theory, (C) competence set analysis and innovation dynamics, (D) group decision making and gaming, (E) second order games, (F) differential games and optimal control theory, and (G) applications. His articles have appeared in numerous prestigious journals. Yu has served as Associate Editor of the Journal of Optimization Theory and Applications since 1977, and as the Area Editor of Operations Research — Decision Making from 1994–1998. He is currently the Chief Editor of Journal of Habitual Domains and is also an advisory editor for a number of academic journals. Po-Lung has given many keynote addresses in different countries to both academic and non-academic audiences. His audiences have included professors, students, corporate executives, ministers, military generals, monks, nuns, housewives, and even prisoners. He enjoys playing basketball, camping, boating, water skiing, roller skating, and exploring the outdoors. Milan Zeleny was born on January 22, 1942 in Czechoslovakia. He received his Dipl. Ing. degree (Quantitative Methods, Political Economy, Finance) in 1964 from the Prague School of Economics. In 1967, he left Czechoslovakia for the United States, traveling on the Queen Elizabeth, to study at the University of Rochester where he received an M.Sc. degree in Systems Management (1970) and a Ph.D. in Business Economics (1972). His doctoral dissertation, entitled “Linear Multiobjective Programming,” was supervised

Milan Zeleny

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by Po-Lung Yu. (This dissertation turned out to be in direct competition with a very similar dissertation of Ralph Steuer; the two then met in South Carolina.) Milan organized the first conference on Multiple Criteria Decision Making in 1972 at the University of South Carolina. Because he did not have his Ph.D. at the time, the Dean “awarded” him assistant professorship status for the duration of the MCDM conference. After the conference Milan returned to complete his Ph.D. He then joined Columbia University in New York, where he edited the Proceedings (with James L. Cochrane), which was published as “Multiple Criteria Decision Making” in 1973 by the University of South Carolina Press. Milan’s first encounter with MCDM was in 1965 when he published “The Multidimensional Model of Complex Technological Projects” (in Czech) as an extension of the RAMPS method. In 1969 his understanding of Czech and Russian helped him expand his knowledge: he read an article of his Czech army colleague, based on an article in Russian, which was translated from German (the name of the original East-German author was Jüttler). Another good source was linear programming of Hungarian Peter Bod. Milan “offered” the MCDM dissertation topic to his fellow student at Rochester — who refused to take it. Milan had his thesis on “Signal Flowgraphs in Economics” just about ready when he decided to switch to MCDM, feeling guilty about “wasting” such a good topic. Prior to joining Fordham University in 1982, Milan Zeleny has held academic appointments at the University of South Carolina, Columbia University, the Copenhagen School of Economics, and the European Institute for Advanced Studies in Management. He is currently a Professor of Management Systems. His concurrent visiting affiliations include the Tomas Bata University (Zlin), the Indian Institute of Technology (Kanpur), Fu Jen University (Taipei), Peking University (Beijing), and most recently, IBMEC (Rio de Janeiro). He has lectured on MCDM in such countries as Finland, Denmark, Italy, Japan, China, South Africa, Brazil, Australia, and New Zealand. In addition to MCDM, Milan has worked on many different research topics. Apart from his work on the multiple criteria simplex method, linear multiobjective programming, de novo programming, different concepts of optimality, compromise programming, knowledge-based

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fuzzy sets, knowledge management, self-producing social systems, spontaneous social orders, high technology management, theory of the displaced ideal, conflict dissolution, multidimensional radar diagrams, osmotic growths, and inorganic precipitates, he has also written historical studies on Trentowski’s Cybernetyka, Bogdanov’s Tectology, Leduc’s Synthetic Biology and Smuts’ Holism; as well as original contributions to management, strategy, systems sciences, cybernetics, autopoiesis, artificial life, multiple-payoffs game theory, APL simulations, social judgment theory, economics of interactions, and trade-off-free economics. A prolific author (his most recent book is Human Systems Management, 2005), he is currently in the process of writing The BioCycle of Business. He has published over 400 essays, stories and newspaper/magazine articles, including a biography of Augustine Herrman, the first Czech in America. Milan’s various editorial responsibilities (having served on more than ten editorial boards — and being fired from many) include serving as the Editor-in-Chief of Human Systems Management for the past 30 years. He has received many awards, including the George Cantor Award from the International Society on MCDM in 1992. He is listed as the most cited scientist among Czech and Slovak economists. Currently he shuttles between the US and the Czech Republic, dividing his work and leisure roughly equally between the two places and cultures. In his “Castanea” in Southern Bohemia he is a “gentleman farmer,” raising white and blue peacocks, pigeons, rabbits, ducks, geese and bees. He has now switched from business consulting to executive coaching, and has formed a team of businessmen and entrepreneurs who follow human systems management. In effect, the team has established an entrepreneurial university, in which they study and practice the Bata Management System (BMS). Stanley Zionts was born in Pittsburgh, Pennsylvania on January 18, 1937. Though his father was educated (an architect), the family was poor. When Stan was five years old, his mother committed suicide, in part a result of post-partum depression shortly after the birth of his sister. Stan’s father remarried roughly three years later. Life was not easy for the family, but the family was not aware that they were poor.

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When Stan was thirteen, he became a caddy at a golf course. Initially he loved golf, but ultimately he gave up the game. Even so, he worked at the country club for about five years, saving more than enough money for two years at a private university. He was a good student in high school and did particularly well in the sciences and mathematics. He applied to the Carnegie Institute of Technology (now Carnegie-Mellon) and was awarded a small scholarship to study electrical engineering. He graduated in 1958 and Stan Zionts immediately joined the Master’s program in Industrial Administration (now Business) at Carnegie. From the age of thirteen, he almost always had part-time jobs, and while he worked on his Master’s degree, he taught calculus to engineers at night school at Carnegie. Because of the large number of military veterans in his classes, he was sometimes the youngest person in the class. After receiving his Master’s degree in 1960, he served in the US Army in Fort Monmouth, NJ for six months and then joined US Steel Corporation in Monroeville, PA. While there he worked as an internal consultant applying operations research models. His experience there led to several publications based on operations research applications. In 1963 he returned to Carnegie to pursue a Ph.D. degree in Industrial Administration. He completed his dissertation entitled “Size Reduction Techniques of Linear Programming and their Applications,” in the summer of 1965, under Gerald L. Thompson and William W. Cooper. He continued working for US Steel while doing his degree. While he was working on his dissertation, he met Bruno Contini. He and Contini worked on a bargaining model involving multiple criteria. They published an article on their work in Econometrica in 1968. After completing his degree, he took a position with the Ford Foundation in Calcutta, India where he recruited and set up a computer organization for the steel industry. This was his first international experience, and he and his wife Terri (and their two children) loved the experience. They traveled widely and began to appreciate travel and

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different cultures. At the end of eighteen months in India (in 1967), Stan accepted a position on the faculty of the School of Management at the State University of New York at Buffalo. As the family had very much enjoyed their experience in India, Stan and Terri began to consider other international opportunities. After six years in Buffalo, Stan accepted a position at the European Institute for Advanced Studies in Management in Brussels, Belgium. There Stan’s responsibilities included working with Ph.D. students from all over Europe, doing research, giving talks on his research, and organizing conferences. Stan met and began working with Jyrki Wallenius there. He organized several conferences, one of which was a conference on Multiple Criteria Decision Making held at CESA in 1975 in Jouy-enJosas, France, organized together with Hervé Thiriez. That conference became the first meeting of the International Society on Multiple Criteria Decision Making. Stan also became the first (founding) President of the Special Interest Group on Multiple Criteria Decision Making, which later evolved into the International Society. On returning from Belgium, Stan Zionts continued his research and teaching at SUNY Buffalo. He also continued his international involvement. Zionts served as Department Chairman in Buffalo and in other administrative roles as well. Zionts became a Distinguished Professor and was the recipient of several awards, including teacher of the year. He was named a Fellow of INFORMS and was awarded an honorary doctorate by the Helsinki School of Economics in 2006. He also was awarded the Gold Medal by the International Society on MCDM. Karwan, Spronk, and Wallenius edited a special volume in honor of Stan Zionts on the occasion of his 60th birthday, in 1997. SUNY Buffalo had the first MBA program in China, and Zionts eagerly participated in it, teaching in three of the school’s programs in Dalian, China. He also taught in a program the school had in Beijing for Motorola, as well as in SUNY international programs in France and Latvia. Zionts’ research work is in the areas of linear and integer programming, multiple criteria decision making, negotiation, finance, and economics. Zionts began to ski shortly after going to Buffalo in 1967. He became passionate about skiing and became a ski instructor over twenty years ago,

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first in Western New York and since 2003 at the Park City Mountain Resort in Utah. Zionts retired from the university in 2005. Among his other activities, he presents pro bono seminars on senior finance, plays duplicate bridge with his wife Terri, and continues academic research with various researchers. He and his wife Terri are also actively involved with their four children and nine grandchildren.

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Conclusion

Our field of multiple criteria decision making (MCDM) is about making choices, supporting those choices, and understanding them, in the presence of multiple, conflicting criteria. In this book we have described the history of MCDM, from its roots to the present. The roots of our field extend to interesting research by early economists and mathematicians, many of whom have received the Nobel Prize in Economics. Our field has contributed to knowledge with such fundamental concepts as Paretooptimality (efficiency), preference modeling, trade-offs, decision traps, among others. We are fortunate to have been part of many central developments in our field over some 40 years. Our involvement began with the Econometrica publication of Bruno Contini and Stan Zionts about the multiple criteria bargaining problem in 1968 and its application to the Indian steel industry. Over the years the three of us have collaborated closely. First Stan and Jyrki, then Stan and Murat, and more recently Jyrki and Murat. When we began our research in MCDM, the field was small. Until the early 1970s there were only a handful of publications. By the end of that decade, the number of annual MCDM ISI publications had grown to about 100; by 1990 to about 200. Since then the growth in the number of publications has been exponential. The annual number of ISI publications today is close to 2000. What has happened? First, our field has penetrated many neighboring disciplines. Secondly, many engineering applications are being developed. The growth of our field can, in part, be attributed to the evolutionary multiobjective optimization (EMO) community. A downside of the tremendous growth is that MCDM research has become fragmented

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into different scholarly communities (schools). Such schools include Multiattribute Utility Theory, Multiple Objective Mathematical Programming, Fuzzy Sets, the French School of decision aiding, Vector Optimization, Goal Programming, EMO, Analytic Hierarchy Process (AHP), and so on. What is happening to our field? Will the growth continue? Will the fragmentation continue? We do not know all the answers. But we would like to offer our advice and venture a few predictions. Obviously, fragmentation without collaboration across schools is not good. At some point the different schools have to learn from each other. “Reinventing the wheel” is wasteful. Bridge builders who can facilitate cooperation between schools are important. As an example of fruitful bridge building, we mention the recent collaboration between EMO and MCDM. Until relatively recently, the interest of EMO scholars was simply in generating an approximation to the Pareto-optimal frontier and stopping there. Now MCDM scholars and EMO scholars are working together to incorporate a decision maker and her preferences (often interactively) into EMO algorithms. The growth of multiple criteria research in different functional fields and in engineering applications is substantial. However, many who apply MCDM concepts and techniques lack the proper training. They at best “reinvent the wheel,” and at worst make serious errors. The future of applications may lie in user-friendly spreadsheet type solvers. But we have to learn to support not only managers, but consumers making choices both online and in other media. Ward Edwards realized this and tried to do it. There are billions more consumers than managers! Much of the decision support will take place in an online environment. The support which is needed may be simpler than what we have grown accustomed to. We agree with Peter Fishburn1 that the overwhelming significance of the classical concept of rationality as understood by economists will gradually erode. We also think that the mainstream MCDM community has not yet realized the significance of behavioral

1

Peter C. Fishburn: “Decision Theory: The Next 100 Years,” The Economic Journal 101, 1991, 27–32.

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issues, despite warning calls by many prominent behavioral decision theorists such as Herbert Simon, Ward Edwards, and Oleg Larichev. We predict that behavioral issues will in the future play a more significant role in our field than they have in the past. MCDM has had a great past; undoubtedly it will have a great future. We wish the best of success to current as well as to future generations of MCDM scholars.

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Afriat, S. (1967). “The construction of a utility function from expenditure data,” International Economic Review 8, 67–77. Airo, S. (1994). “Approximating the Nondominated Set with the Simple Genetic Algorithm (SGA),” Working Paper, Helsinki School of Economics. Aksoy, Y. (1990). “Interactive multiple objective decision making: A bibliography (1965–1988),” Management Research News 13, 1–8. Aneja, Y.P. and Nair, K.P.K. (1979). “Bicriteria transportation problem,” Management Science 25(1), 73–78. Arbel, A. (1989). “Approximate articulation of preference and priority derivation,” European Journal of Operational Research 43(3), 317–326. Arrow, K. (1951). Social Choice and Individual Values, Wiley & Sons, New York. Balibek, E. and Köksalan, M. (2010). “A multi-objective multi-period stochastic programming model for public debt management,” European Journal of Operational Research 205, 205–217. Bana e Costa, C. (1992). Structuration, Construction et Exploitation d’un Modele Multicritere d’Aide a la Decision, Ph.D. thesis, Technical University of Lissabon. Bana e Costa, C., De Corte, J.-M., and Vansnick, J.-C. (2005). “On the mathematical foundation of MACBETH,” in Multiple Criteria Decision Analysis: State of the Art Surveys, Figueira, J., Greco, S., and Ehrgott, M. (Eds.), Springer, New York. Bell, D. (1973). The Resolution of Duality Gaps in Discrete Optimization, Ph.D. thesis, MIT. Bell, D. (1982). “Regret in decision-making under uncertainty,” Operations Research 30(5), 961–981.

161

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Bell, D.E., Keeney, R.L., and Raiffa, H. (Eds.) (1977). Conflicting Objectives in Decisions. John Wiley & Sons, New York. Bell, D.E., and Schleifer Jr., A. (1996). Decisions under Uncertainty. 2nd Ed. Cambridge, Mass.: Course Technology Inc. (CTI). Belton, V. (1992). “Integrating Data Envelopment Analysis with Multiple Criteria Decision Analysis,” in MCDM, Goicoechea, A., Duckstein, L., and Zionts S. (Eds.), 71–79, Springer, Berlin. Belton, V. and Stewart, T. (2002). Multiple Criteria Decision Making: An Integrated Approach, Kluwer Academic Publishers, Boston. Belton, V. and Vickers, S.P. (1989). “V.I.S.A — VIM for MCDA,” in Improving Decision Making in Organisations, Lockett, G. and Islei, G. (Eds.), 287–304, Springer Verlag, Berlin, Heidelberg. Benayoun, R., de Montgolfier, J., and Keuneran, D. (1970). “Mathematical programming with multi-objective functions: A solution by P.O.P. (Progressive Orientation Procedure),” Revue Metra 9(2), 279–299. Benayoun, R., de Montgolfier, J., Tergny, J., and Larichev, O. (1971). “Linear programming with multiple objective functions: Step-method (STEM),” Mathematical Programming 1(3), 366–375. Benson, H.P. (1995). “A geometrical analysis of the efficient outcome set in multiple objective convex programs with linear criterion functions,” Journal of Global Optimization 6, 231–251. Benson, H.P. (1998). “Hybrid approach for solving multiple-objective linear programs in outcome space,” Journal of Optimization Theory and Applications 98(1), 17–35. Benson, H.P. and Sayin, S. (1993). “A face search heuristic algorithm for optimizing over the efficient set,” Naval Research Logistics 40, 103–116. Benson, H.P. and Sun, E.J. (2002). “A weight set decomposition algorithm for finding all efficient extreme points in the outcome set of a multiple objective linear program,” European Journal of Operational Research 139, 26–41. Bitran, G. (1977). “Linear multiple objective programs with zero-one variables,” Mathematical Programming 13(1), 121–139. Bouyssou, D., Jacquet-Lagrèze, É., Perny, P., Słowiński, R., Vanderpooten, D. and Vincke, P. (Eds.) (2002). Aiding Decisions with Multiple Criteria: Essays in Honour of B. Roy, Kluwer, Dordrecht. Bouyssou, D. and Marchant, T. (2007). “An axiomatic approach to noncompensatory sorting methods in MCDM, II: More than two categories,” European Journal of Operational Research 178, 246–276.

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References

163

Bouyssou, D. and Pirlot, M. (2009). “An axiomatic analysis of concordancediscordance relations,” European Journal of Operational Research 199(2), 468–477. Bragge, J., Korhonen, P., Wallenius, H., and Wallenius, J. (2009). “Bibliometric Analysis of Multiple Criteria Decision Making/Multiattribute Utility Theory,” in IXX International MCDM Conference Proceedings, Ehrgott, M., Naujoks, B., Stewart, T., and Wallenius, J., (Eds.), Springer, Berlin. Brams, S. and Fishburn, P. (1978). “Approval voting,” American Political Science Review 72(3), 831–847. Brams, S.J., Gehrlein, W.V., and Roberts, F.S. (Eds.) (2009). The Mathematics of Preference, Choice and Order: Essays in Honor of Peter C. Fishburn, Springer-Verlag, Berlin, Heidelberg. Branke, J., Greco, S., Słowiński, R., and Zielniewicz, P. (2009). “Interactive Evolutionary Multiobjective Optimization Using Robust Ordinal Regression,” in EMO ‘09: Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization, 554–568, Springer-Verlag, Berlin, Heidelberg. Brans, J.P., Vincke, P., and Mareschal, B. (1986). “How to select and how to rank projects: The PROMETHEE method,” European Journal of Operational Research 28, 228–238. Carlsson, C. and Korhonen, P. (1986). “A parametric approach to fuzzy linearprogramming,” Fuzzy Sets and Systems 20(1), 17–30. Chankong, V. and Haimes, Y.Y. (1983). Multiobjective Decision Making: Theory and Methodology, North-Holland Publishing, New York, Amsterdam. Charnes, A. (1952). “Optimality and degeneracy in linear programming,” Econometrica 20(2), 160–170. Charnes, A. and Cooper, W.W. (1961). Management Models and Industrial Applications of Linear Programming, Wiley, New York. Charnes, A., Cooper, W.W., and Ferguson, R.O. (1955). “Optimal estimation of executive compensation by linear programming,” Management Science 1, 138–151. Charnes, A., Cooper, W. W., and Henderson, A. (1953). An Introduction to Linear Programming. Wiley, New York. Charnes, A., Cooper, W.W., and Mellon, B. (1952). “Blending aviation gasolines — a study in programming interdependent activities,” Econometrica 20, 135–159.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

164

Page 164

Multiple Criteria Decision Making

M. Köksalan, J. Wallenius and S. Zionts

Charnes, A., Cooper, W.W., and Rhodes, E. (1978). “Measuring the efficiency of decision making units,” European Journal of Operational Research 2, 429–444. Churchman, C.W. and Ackoff, R.L. (1954). “An approximate measure of value,” Operations Research 2, 172–187. Climaco, J. and Martins, E. (1982). “A bicriterion shortest path algorithm,” European Journal of Operational Research 11(4), 399–404. Cochrane, J.L. and Zeleny, M. (Eds.) (1973). Multiple Criteria Decision Making, University of South Carolina Press, Columbia. Coello, C.A.C. (2000). “Handling Preferences in Evolutionary Multiobjective Optimization: A Survey,” in Proceedings of the 2000 Congress on Evolutionary Computation, 30–37, Piscataway, NJ. IEEE Service Center. Coello, C.A.C. and Lamont, G.B. (2004). Applications of Multi-Objective Evolutionary Algorithms, World Scientific, Singapore. Coello, C.A.C., Lamont, G.B., and Veldhuizen, D.A.V. (2006). Evolutionary Algorithms for Solving Multi-Objective Problems, Springer, Berlin. Cohon, J.L. (1978). Multiobjective Programming and Planning, Academic Press, New York. Cohon, J.L. and Marks, D.H. (1973). “Multiobjective screening models and water resource investment,” Water Resources Research 9(4), 826–836. Condorcet, N. (1785). Essay on the Application of Analysis to the Probability of Majority Decisions, Bibliotheque national de France. Contini, B. and Zionts, S. (1968). “Restricted bargaining for organizations with multiple objectives,” Econometrica 36, 397-414. Costa, M.G., Captivo, M.E., and Clímaco, J. (2008). “Capacitated single allocation hub location problem — A bicriteria approach,” Computers & Operations Research 35(11), 3671–3695. Da Cunha, N.O. and Polak, E. (1967). “Constrained minimization under vectorvalued criteria in finite dimensional spaces,” Journal of Mathematical Analysis and Applications 19(1), 103–124. Dantzig, G.B. (1948). “Linear Programming,” in Problems for the Numerical Analysis of the Future, Proceedings of the Symposium on Modern Calculating Machinery and Numerical Methods, UCLA, July 29–31. Dantzig, G. and Saaty, T.L. (1973). Compact City: A Plan for a Liveable Urban Environment, W.H. Freeman, San Francisco.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

Page 165

Multiple Criteria Decision Making

References

165

Dauer, J.P. (1991). “Optimization over the efficient set using an active constraint approach,” ZOR — Methods and Models of Operations Research 35, 185–195. Dauer, J.P. and Gallagher, R.J. (1996). “A combined constraint space, objective space approach for determining high-dimensional maximal efficient faces of multiple objective linear programs,” European Journal of Operational Research 88, 368–381. de Neufville, R. and Keeney, R.L. (1974). “Use of Decision Analysis in Airport Development for Mexico City,” in Analysis of Public Systems, Drake, A.W., Keeney, R.L., and Morse, P.M. (Eds.), M.I.T. Press, Cambridge, Massachusetts. Deb, K. (2001). Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, New York. Deb, K. and Köksalan, M. (2010) “Preference-based multiobjective evolutionary algorithms,” IEEE Transactions on Evolutional Computation 14(5), 669–670. Deb, K. and Kumar, A. (2007). “Interactive Evolutionary Multi-Objective Optimization and Decision-Making using Reference Direction Method,” in 2007 Genetic and Evolutionary Computation Conference (GECCO’2007), 1, Thierens, D. (Ed.), 781–788, ACM Press, London, UK. Deb, K., Mohan, M., and Mishra, S. (2005). “Evaluating the ε-domination based multi-objective evolutionary algorithm for a quick computation of paretooptimal solutions,” Evolutionary Computation 13(4), 501–525. Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T. (2002). “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Transactions on Evolutionary Computation 6(2), 182–197. Deb, K. and Sundar, J. (2006). “Reference Point Based Multi-Objective Optimization Using Evolutionary Algorithms,” in 2006 Genetic and Evolutionary Computation Conference (GECCO’2006), 1, Cattolico, M. (Ed.), 635–642, ACMPress, Seattle, Washington. Debreu, G. (1959). Theory of Value: An Axiomatic Analysis of Economic Equilibrium, Yale University Press, New Haven. Debreu, G. (1960). “Topological Methods in Cardinal Utility Theory,” in Mathematical Methods in the Social Sciences, Arrow, K., Karlin, S., and Suppes, P. (Eds.), Stanford University Press, Palo Alto, CA. Doyle, R.H. and Green, J.R. (1993). “DEA and MCDM,” OMEGA 6, 713–715.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

166

Page 166

Multiple Criteria Decision Making

M. Köksalan, J. Wallenius and S. Zionts

Dyer, J. (1973). “A time sharing computer program for the solution of the multiple criteria problem,” Management Science 19(12), 1379–1383. Dyer, J.S., Fishburn, P.C., Steuer, R.E., Wallenius, J., and Zionts, S. (1992). “Multiple criteria decision making, multiattribute utility theory: The next ten years,” Management Science 58(5), 645–654. Dyer, J. and Sarin, R. (1979). “The measurable multiattribute value function,” Operations Research 27(4), 810–822. Dyson, R.G. and Thanassoulis, E. (1988). “Reducing weight flexibility in data envelopment analysis,” Journal of the Operational Research Society 39, 563–576. Edgeworth, F. (1881). Mathematical Psychics: An Essay on the Application of Mathematics to the Moral Sciences, C. Kegan Paul and Co., London. Available online at http://socserv2.mcmaster.ca/~econ/ugcm/3ll3/edgeworth/ mathpsychics.pdf Edwards, W. (1954). “The theory of decision making,” Psychological Bulletin 51(4), 380–417. Edwards, W. (1961). “Behavioral decision theory,” Annual Review of Psychology 12, 473–498. Edwards, W. (1962). “Subjective probabilities inferred from decisions,” Psychological Review 69(2), 109–135. Edwards, W. (1971). “Social utilities,” Engineering Economist (Summer Symposium Series) 6, 119–129. Edwards, W. (1977). “How to use multiattribute utility measurement for social decision making,” IEEE Transactions on Systems, Man and Cybernetics SMC — 7, 326–340. Edwards, W., Lindman, H., and Savage, L.J. (1963). “Bayesian statistical inference for psychological research,” Psychological Review 70, 193–242. Edwards, W., Miles, R.F. Jr., and von Winterfeldt, D. (Eds.) (2007). Advances in Decision Analysis: From Foundations to Applications, Cambridge University Press, Cambridge. Ehrgott, M. and Gandibleux, X. (2002). “Multiobjective Combinatorial Optimization,” Chapter 8, in Multiple Criteria Optimization, State of the Art Annotated Bibliographic Surveys, Ehrgott and Gandibleux (Eds.), 369–444, Springer, Berlin. Ehtamo, H., Kettunen, E., and Hämäläinen, R. (2000). “Searching for joint gains in multi-party negotiations,” European Journal of Operational Research 127(1), 54–69.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

Page 167

Multiple Criteria Decision Making

References

167

Eschenauer, H., Koski, J., and Osyczka, A. (Eds.) (1990). Multicriteria Design Optimization: Procedures and Applications, Springer, Berlin. Evans, G.W. (1984). “An overview of techniques for solving multiobjective mathematical programs,” Management Science 30(11), 1268–1282. Evans, J. and Steuer, R.E. (1973). “A revised simplex method for linear multiple objective programs,” Mathematical Programming 5(1), 54–72. Fandel, G. (1975). “Lösungsprinzipien und lösungsalgorithmen zum vektormaximumproblem bei sicherheit und unsicherheit,” Zeitschrift für Betriebswirtschaft 6, 371–392. Fandel, G. and Gal, T. (2001). “Redistribution of funds for teaching and research among universities: The case of North Rhine-Westphalia,” European Journal of Operational Research 130(1), 111–120. Fandel, G. and Gehring, H. (Eds.)(1991). Operations Research Beiträge zur quantitativen Wirtschaftsforschung, Springer-Verlag, Berlin. Farquhar, P.H. (1983). “Research Directions in Multiattribute Utility Analysis,” in Essays and Surveys on Multiple Criteria Decision Making, Hansen, P. (Ed.), 63–85, Springer-Verlag, Berlin. Feeny, D., Furlong, W., Boyle, M., and Torrance, G.W. (1995). “Multi-attribute health status classification systems,” Pharmaco Economics 7(6), 490–502. Feillet, D., Dejax, P., and Gendreau, M. (2005). “Traveling salesman problems with profits,” Transportation Science 39(2), 188–205. Fishburn, P.C. (1964). Decision and Value Theory, Publications in Operations Research, No. 10, Wiley & Sons, New York. Fishburn, P.C. (1970). Utility Theory for Decision Making, Publications in Operations Research, No. 18, Wiley and Sons, New York. Fishburn, P.C. (1973). The Theory of Social Choice, Princeton University Press, Princeton, NJ. Fishburn, P.C. (1982). The Foundations of Expected Utility, Reidel, Dordrecht. Fishburn, P.C. (1988). Nonlinear Preference and Utility Theory, Johns Hopkins University Press, Baltimore. Fishburn, P.C. (1991). “Decision theory: The next 100 years,” The Economic Journal 101, 27–32. Fonseca, C. (1995). Multiobjective Genetic Algorithms with Application to Control Engineering Problems, Ph.D. thesis, Department of Automatic Control and Systems Engineering, University of Sheffield, UK.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

168

Page 168

Multiple Criteria Decision Making

M. Köksalan, J. Wallenius and S. Zionts

Fonseca, C. and Fleming, P. (1993). “Genetic Algorithms for Multiobjective Optimization: Formulation, Discussion, and Generalization,” Proceedings of Fifth International Conference of Genetic Algorithms, Forrest, S. (Ed.), 416–423, Morgan Kaufmann, San Mateo, CA. Forman, E. and Gass, S. (2001). “Analytic hierarchy process: An exposition,” Operations Research 49(4), 469–486. Franklin B. (1772). Letter to Joseph Priestly. Reprinted in the Benjamin Franklin Sampler, 1956. Fawcett, New York. Frisch, R. (1961). “Numerical determination of a quadratic preference function for use in macroeconomic programming,” Giornale Degli Economisti e Annali Di Economica 20, 3–43. Gal, T. and Nedoma, J. (1972). “Multiparametric linear programming,” Management Science 18(7), 406–422. Gass, S. (1958). Linear Programming, McGraw Hill, New York. Gass, S. and Assad, A.A. (2005). An Annotated Timeline of Operations Research: An Informal History, Kluwer, Boston. Gass, S. and Saaty, T. (1955). “Parametric objective function part II,” Operations Research 3, 316–319. Geoffrion, A.M. (1965). A Parametric Programming Solution to the Vector Maximum Problem with Applications to Decisions under Uncertainty, Ph.D. thesis, Stanford University, OR Program. Geoffrion, A.M. (1967). “Solving bi-criterion mathematical programs,” Operations Research 15(1), 39–54. Geoffrion, A.M. (1968). “Proper efficiency and the theory of vector maximization,” Journal of Mathematical Analysis and Applications 22(3), 618–630. Geoffrion, A., Dyer, J., and Feinberg, A. (1972). “An interactive approach for multicriterion optimization with an application to the operation of an academic department,” Management Science 19(4), 357–368. Goicoechea, A., Hansen, D.R., and Duckstein, L. (1982). Multiobjective Decision Analysis with Engineering and Business Applications, Wiley & Sons, New York. Greco, S., Matarazzo, B., and Słowiński, R. (1999). “The Use of Rough Sets and Fuzzy Sets in MCDM,” in Gal T., Stewart T., and Hanne, T. (Eds.), Advances in Multiple Criteria Decision Making, 14.1–14.59, Kluwer Academic Publishers, Dordrecht.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

Page 169

Multiple Criteria Decision Making

References

169

Greco, S., Matarazzo, B., and Słowiński, R. (2001). “Rough set theory for multicriteria decision analysis,” European Journal of Operational Research 129, 1–47. Greco, S., Matarazzo, B., and Słowiński, R. (2002). “Rough sets methodology for sorting problems in presence of multiple attributes and criteria,” European Journal of Operational Research 138, 247–259. Green, P. and Rao, V.R. (1971). “Conjoint measurement for quantifying judgmental data,” Journal of Marketing Research 8, 355–363. Haimes, Y. (2009). Risk Modeling, Assessment, and Management, Wiley & Sons, New York. Haimes, Y. and Hall, W. (1974). “Multiobjectives in water resources systems analysis: The surrogate worth trade-off method,” Water Resources Research 10, 615–624. Haimes, Y., Hall, W., and Friedman, H. (1975). Multiobjective Optimization in Water Resources Systems, Elsevier, Amsterdam. Hallerbach, W.G. and Spronk, J. (2002). “The relevance of MCDM for financial decisions,” Journal of Multi-Criteria Decision Analysis 11(4–5), 187–195. Halme, M., Joro, T., Korhonen, P., Salo, S., and Wallenius, J. (1999). “A value efficiency approach to incorporating preference information in data envelopment analysis,” Management Science 45, 103–115. Hämäläinen, R.P. (1977). Optimal Controller Design by Nonlinear and Game Theoretic Methods, Ph.D. thesis, Acta Polytechnica Scandinavica, Mathematics and Computer Science Series No. 28, Helsinki University of Technology. Hämäläinen, R.P. and Pöyhönen, M. (1996). “Online group decision support by preference programming in traffic planning,” Group Decision and Negotiation 5(4–6), 485–500. Hammond, J.S., Keeney, R.L., and Raiffa, H. (1998). “Even swaps: A rational method for making trade-offs,” Harvard Business Review 76, 137–149. Hammond, J.S., Keeney, R., and Raiffa, H. (1998). “The hidden traps in decision making,” Harvard Business Review (September-October) 47–58. Hammond, J.S., Keeney, R., and Raiffa, H. (1999). Smart Choices: A Practical Guide to Making Better Decisions, Harvard Business School Press, Boston, MA. Hannan, E.L. (1981). “Linear programming with multiple fuzzy goals,” Fuzzy Sets and Systems 3, 522–531. Harker, P.T. and Vargas, L.G. (1987). “The theory of ratio scale estimation: Saaty’s analytic hierarchy process,” Management Science 33(11), 1383–1403.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

170

Page 170

Multiple Criteria Decision Making

M. Köksalan, J. Wallenius and S. Zionts

Henig, M. (1986). “The shortest path problem with two objective functions,” European Journal of Operational Research 25, 281–291. Hobbs, B.F. and Meier, P. (2000). Energy Decisions and the Environment: A Guide to the Use of Multicriteria Methods, Kluwer Academic Publishers, Norwell, Massachusetts. Hoogeveen, J.A. (1992). Single Machine Bicriteria Scheduling, Unpublished Ph.D. thesis, CWI, Amsterdam. Hora, S. and von Winterfeldt, D. (1997). “Nuclear waste and future societies: A look into the deep future,” Technological Forecasting and Social Change 56, 155–170. Horn, J., Nafploitis, N., and Goldberg, D. (1994). “A Niched Pareto Genetic Algorithm for Multi-Objective Optimization,” in Proceedings of the First IEEE Conference on Evolutionary Computation, 82–87. Howard, R. and Kimball, G.E. (1959). “Sequential Decision Processes,” in Notes on Operations Research, Technology Press Cambridge, MA. Howard, R. and Matheson, J.E. (1966). “Decision Analysis: Applied Decision Theory,” in Proceedings of the Fourth International Conference on Operational Research, Wiley-Interscience, 55–71. Hsieh, T.-Y., Lu, S.-T., and Tzeng, G.-H. (2004). “Fuzzy MCDM approach for planning and design tenders selection in public office buildings,” International Journal of Project Management 22(7), 573–584. Ignizio, J. (1976). Goal Programming and Extensions, Lexington Books, Lexington, MA. Ignizio, J. (1982). Linear Programming in Single & Multiple-objective Systems, Prentice-Hall, Englewood Cliffs, NJ. Ijiri, Y. (1965). Management Goals and Accounting for Control, Rand McNally, Chicago. Isermann, H. (1977). “The enumeration of the set of all efficient solutions for a linear multiple objective program,” Operational Research Quarterly 28(3), 711–725. Ishibuchi, H. and Murata, T. (1998). “Multi-objective genetic local search algorithm and its application to flow shop scheduling,” IEEE Transactions on Systems, Man & Cybernetics Part C: Applications and Reviews 28(3), 392–403. Jacquet-Lagreze, E. (1995). “An Application of the UTA Discriminant Model for the Evaluation of R&D Projects,” in Advances in Multicriteria Analysis,

b1148_References.qxd

5/5/2011

6:31 AM

b1148

Page 171

Multiple Criteria Decision Making

References

171

Pardalos, P.M., Siskos, Y., and Zopounidis, C. (Eds.), 203–211, Kluwer Academic Publishers, Dordrecht. Jacquet-Lagreze, E. and Siskos, Y. (1982). “Assessing a set of additive utility functions for multicriteria decision-making, the UTA method,” European Journal of Operational Research 10, 151–164. Joro, T., Korhonen, P., and Wallenius, J. (1998). “Structural comparison of data envelopment analysis and multiple objective linear programming,” Management Science 44, 962–970. Kahneman, D. and Tversky, A. (1979). “Prospect theory: An analysis of decision under risk,” Econometrica 47, 262–291. Kantorovich, L. (1939). “Mathematical Methods of Organizing and Planning Production,” published in English (1960) in Management Science 6(4), 363–422. Karahan, I. and Köksalan, M. (2010). “A territory defining multiobjective evolutionary algorithm and preference incorporation,” IEEE Transactions on Evolutionary Computation, 14(4), 636–664. Karasakal, E.K. and Köksalan, M. (2009). “Generating a representative subset of the efficient frontier in multiple criteria decision making,” Operations Research 57, 187–199. Karwan, M.H., Spronk, J., and Wallenius, J. (1997). Essays in Decision Making, Springer, Berlin. Keeney, R. (1972). “Utility functions for multiattributed consequences,” Management Science 18(5), 276–287. Keeney, R. (1992). Value Focused Thinking, Harvard University Press, Cambridge, Massachusetts. Keeney, R. and Raiffa, H. (1976). Decisions with Multiple Objectives: Preferences and Value Tradeoffs, Wiley, New York. Keeney, R., von Winterfeldt, D., and Eppel, T. (1990). “Eliciting public values for complex policy decisions,” Management Science 36(9), 1011–1030. Kersten, G., Michalowski, W., Cray, D., and Lee, I. (1991). “An analytic basis for decision support in negotiations,” Naval Research Logistics 38, 743–761. Kersten, G., Michalowski, W., Szpakowicz, S., and Koperczak, Z. (1991). “Restructurable representations of negotiation,” Management Science 37(10), 1269–1290. Kirkwood, C.W. (1997). Strategic Decision Making: Multiobjective Decision Analysis with Spreadsheets, Duxbury Press, Belmont, CA.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

172

Page 172

Multiple Criteria Decision Making

M. Köksalan, J. Wallenius and S. Zionts

Kirkwood, C.W. and Sarin, R. (1985). “Ranking with partial information: A method and an application,” Operations Research 33(1), 38–48. Klinger, A. (1964). “Vector-valued performance criteria,” IEEE Transactions on Automatic Control AC-9(1), 117–118. Köksalan, M. (1980). Fuzzy Programming in Multiobjective Planning Problems, M.S. thesis, IE Dept., Middle East Technical University, Ankara, Turkey. Köksalan, M. (1999). “A heuristic approach to bicriteria scheduling,” Naval Research Logistics 46, 777–789. Köksalan, M., Azizoglu, M., and Kondakci, S. (1998). “Minimizing flowtime and maximum earliness on a single machine,” IIE Transactions 30, 192–200. Köksalan, M. and Karahan, I. (2010). “An interactive territory defining evolutionary algorithm: iTDEA,” IEEE Transactions on Evolutionary Computation 14(5), 702–722. Köksalan, M.M., Karwan, M.H., and Zionts, S. (1984). “An improved method for solving multiple criteria problems involving discrete alternatives,” IEEE Transactions on Systems, Man and Cybemetics SMC-14(1), 24–34. Köksalan, M. and Lokman, B. (2009). “Approximating the nondominated frontiers of multi-objective combinatorial optimization problems,” Naval Research Logistics 56, 191–198. Köksalan, M. and Özpeynirci, B.S. (2009). “An interactive sorting method for additive utility functions,” Computers and Operations Research 36, 2565–2572. Köksalan, M. and Plante, R.D. (2003). “Interactive multi-criteria optimization for multiple response product and process design,” Manufacturing and Service Operations Management 5(4), 334–347. Köksalan, M.M. and Sagala, P.N.S. (1995a). “Interactive approaches for discrete alternative multiple criteria decision making with monotone utility functions,” Management Science 41, 1158–1171. Köksalan, M.M. and Sagala, P.N.S. (1995b). “An approach and computational results on testing the form of a decision maker’s utility function,” Journal of Multi-Criteria Decision Analysis 4, 189–202. Köksalan, M. and Soylu, B. (2010). “Bicriteria p-hub location problem and evolutionary algorithms,” INFORMS Journal on Computing, forthcoming. Köksalan, M. and Ulu, C. (2003). “An interactive approach for placing alternatives in preference classes,” European Journal of Operational Research 144, 429–439.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

Page 173

Multiple Criteria Decision Making

References

173

Koo, A.Y.C. (1963). “An empirical test of revealed preference theory,” Econometrica 31(4), 646–664. Koopmans, T.C. (1951). “Analysis of Production as an Efficient Combination of Activities,” in Activity Analysis of Production and Allocation, Koopmans, T.C. (Ed.), Physica Verlag, Heidelberg. Korhonen, P. (1977). A Stepwise Procedure for Multivariate Clustering, Ph.D. thesis, Computing Centre, University of Helsinki. Korhonen, P. (1988). “A visual reference direction approach to solving discrete multiple criteria problems,” European Journal of Operational Research 34(2), 152–159. Korhonen, P. and Laakso, J. (1986). “A visual interactive method for solving the multiple criteria problem,” European Journal of Operational Research 24, 277–287. Korhonen, P., Moskowitz, H., and Wallenius, J. (1990). “Choice behavior in interactive multiple-criteria decision making,” Annals of Operations Research 23, 161–179. Korhonen, P., Moskowitz, H., and Wallenius, J. (1992). “Rocky road from a draft into a published scientific journal article in the management and decision sciences,” Krannert Graduate School of Management, Institute for Research in the Behavioral, Economic, and Management Sciences, Purdue University. Korhonen, P. and Wallenius, J. (1988). “A Pareto Race,” Naval Research Logistics 35, 615–623. Korhonen, P., Wallenius, J., and Zionts, S. (1980). “A Bargaining Model for Solving the Multiple Criteria Problem,” Lecture Notes in Economics and Mathematical Systems 177, Multiple Criteria Decision Making Theory and Application, Fandel, G. and Gal, T. (Eds.), 178–188, Springer, Berlin. Korhonen, P., Wallenius, J., and Zionts, S. (1984). “Solving the discrete multiple criteria problem using convex cones,” Management Science 30(11), 1336–1345. Kornbluth, J. and Steuer, R.E. (1981). “Multiple objective linear fractional programming,” Management Science 27(9), 1024–1039. Kuhn, H.W. and Tucker, A.W. (1951). “Nonlinear Programming,” in Proceedings of the Second Berkeley Symposium on Mathematical Statistics and Probability, University of California Press, Berkeley, CA. Lahdelma, R., Salminen, P., and Hokkanen, J. (2000). “Using multicriteria methods in environmental planning and management,” Environmental Management 26, 595–605.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

174

Page 174

Multiple Criteria Decision Making

M. Köksalan, J. Wallenius and S. Zionts

Larichev, O. and Moshkovich, H. (1994). “An approach to ordinal classification problems,” International Transactions in Operational Research 1, 375–385. Larichev, O. and Moshkovich, H. (1997). Verbal Decision Analysis for Unstructured Problems, Springer, Berlin. Larichev, O. and Olson, D. (2001). Multiple Criteria Analysis in Strategic Siting Problems, Kluwer, Boston. Lee, S.M. (1972). Goal Programming for Decision Analysis, Auerbach Publishers, Philadelphia. Lee, W., Tzeng, G., Hsu, C., Huang, J. (2009). “Combined MCDM techniques for exploring stock selection based on Gordon model,” Expert Systems With Applications 36(3), Part 2, 6421–6430. Lieberman, E. (1991). “Soviet multi-objective mathematical programming methods: An overview,” Management Science 37(9), 1147–1165. Lieberman, E. (1991). Multi-Objective Programming in the USSR, Academic Press, New York. Loomes, G. and Sugden, R. (1982). “Regret theory: An alternative theory of rational choice under uncertainty,” Economic Journal 92(4), 805–824. Lotfi, V., Stewart, T.J., and Zionts, S. (1992). “An aspiration-level interactive model for multiple criteria decision making,” Computers and Operations Research 19(7), 671–681. Lotov, A. (1972). “Numerical method of constructing attainability sets for a linear control system,” USSR Journal of Computational Mathematics and Mathematical Physics 12(3), 785–788. Lotov, A. (1984). Introduction into Mathematical Modeling of Economic Systems, Nauka Publishing House, Moscow. Lotov, A., Bushenkov, V., and Kamenev, G. (2004). Interactive Decision Maps, Approximation and Visualization of the Pareto Frontier, Kluwer, Boston. Lotov, A. and Pospelova, I. (2008). Multiobjective Decision Making, published in Russian by MAKS Press, Moscow. Luce, R.D. and Raiffa, H. (1957). Games and Decisions: Introduction and Critical Survey, Wiley & Sons, New York. Luce, R.D. and Tukey, J.W. (1964). “Simultaneous conjoint measurement: A new type of fundamental measurement,” Journal of Mathematical Psychology 1, 1–27. Maes, P., Guttman, R., and Moukas, A.G. (1999). “Agents that buy and sell: Transforming commerce as we know it,” Communications of the Association for Computing Machinery 42(3), 81–91.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

Page 175

Multiple Criteria Decision Making

References

175

Malakooti, B. (1989). “Theories and an exact interactive paired-comparison approach for discrete multiple criteria problems,” IEEE Transactions on Systems, Man and Cybernetics SMC-19, 365–378. Matwin, S., Szpakowicz, S., Koperczak, Z., Kersten, G., and Michalowski, W. (1989). “Negoplan: An expert system shell for negotiation support,” IEEE Expert: Intelligent Systems and Their Applications 4(4), 50–62. Merkhofer, M. and Keeney, R. (1987). “A multiattribute utility analysis of alternative sites for the disposal of nuclear waste,” Risk Analysis 7(2), 173–194. Mesarovic, M.D. (1964). Views on General Systems Theory, Wiley & Sons, New York. Michalowski, W. and Szapiro, T. (1992). “A bi-reference procedure for interactive multiple criteria programming,” Operations Research 40 (2), 247–258. Miettinen, K. (1999). Nonlinear Multiobjective Optimization, Kluwer, Boston. Miettinen, K. and Mäkelä, M.M. (1995). “Interactive bundle-based method for nondifferentiable multiobjective optimization: NIMBUS,” Optimization 34, 231–246. Mousseau, V. and Słowiński, R. (1998). “Inferring an ELECTRE TRI Model from Assignment Examples,” Journal of Global Optimizaion 12, 157–174. Nakayama, H. and Sawaragi, Y. (1984). “Satisficing Trade-off Method for Multiobjective Programming,” in Interactive Decision Analysis, Grauer, M. and Wierzbicki, A.P. (Eds.), 113–122, Springer-Verlag, New York. Nakayama, H., Yun, Y., and Yoon, M. (2009). Sequential Approximate Multiobjective Optimization Using Computational Intelligence, SpringerVerlag, Berlin. Nash, J. (1950a). “Equilibrium points in n-person games,” in Proceedings of the National Academy of Sciences of the United States of America 36(1), 48–49. Nash, J. (1950b). “The Bargaining Problem,” Econometrica 18(2), 155–162. Nickel, S., Puerto, J., and Rodríguez-Chía, A.M. (2005). “MCDM Location Pproblems,” in Multiple Criteria Decision Analysis: State of The Art Surveys, Figuera, J., Greco, S., and Ehrgott, M. (Eds), 761–795, Springer. Olson, D. (1996). Decision Aids for Selection Problems, Springer, Berlin. Opricovic, S. and Tzeng, G-H. (2003). “Fuzzy multicriteria model for postearthquake land-use planning,” Natural Hazards Review 4(2), 59–64. Opricovic, S. and Tzeng, G-H. (2004). “Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS,” European Journal of Operational Research 156(2), 445–455.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

176

Page 176

Multiple Criteria Decision Making

M. Köksalan, J. Wallenius and S. Zionts

Ozernoy, V.M. (1988). “Multiple criteria decision making in the USSR: A survey,” Naval Research Logistics 36, 543–566. Özpeynirci, Ö. and Köksalan, M. (2009). “Multiobjective traveling salesperson problem on Halin graphs,” European Journal of Operational Research 196, 155–161. Pareto, V. (1896–1897). Cours d’économie politique, Universite de Lausanne. Pareto, V. (1906). Manual of Political Economy, Societa Editrice Libraria, Milano. Pawlak, Z. (1982). “Rough sets,” International Journal of Computer & Information Science 11, 341–356. Peng, Y., Kou, G., Shi, Y., and Chen, Z. (2008). “A multi-criteria convex quadratic programming model for credit data analysis,” Decision Support Systems 44, 1016–1030. Phelps, S.P. and Köksalan, M. (2003). “An interactive evolutionary metaheuristic for multiobjective combinatorial optimization,” Management Science 49(12), 1726–1738. Phillips, L.D. and von Winterfeldt, D. (2007). “Reflections on the Contributions of Ward Edwards to Decision Analysis and Behavioral Research,” in Advances in Decision Analysis: From Foundations to Applications, Edwards, Miles, and von Winterfeldt (Eds.), Cambridge University Press, Cambridge. Raiffa, H. (1968). Decision Analysis, Introductory Lectures on Choices under Uncertainty, Addison-Wesley, Reading, MA. Raiffa, H. (1982). The Art and Science of Negotiation. Harvard University Press, Cambridge, MA. Raiffa, H. (2007). Negotiation Analysis: The Science and Art of Collaborative Decision Making, with contributions of Richardson, J. and Metcalfe, D., Harvard University Press, Cambridge, MA. Raiffa, H. and Schlaifer, R. (1961). Applied Statistical Decision Theory, Wiley & Sons, New York. Raith, A. and Ehrgott, M. (2009). “A comparison of solution strategies for biobjective shortest path problems,” Computers and Operations Research 36(4), 1299–1331. Ramesh, R., Zionts, S., and Karwan, M.H. (1986). “A class of practical interactive branch-and-bound algorithms for multicriteria integer programming,” European Journal of Operational Research 26, 161–172.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

Page 177

Multiple Criteria Decision Making

References

177

Ramsey, F.P. (1931). “Truth and Probabilty,” in The Foundations of Mathematics and Other Logical Essays, Routledge and Kegan, London, 156–198. Romero, C. (1986). “A survey of generalized goal programming (1970–1982),” European Journal of Operational Research 25, 183–191. Romero, C. and Rehman, T. (1984). “Goal programming and multiple criteria decision making in farm planning: An expository analysis,” Journal of Agricultural Economics 35, 177-190. Romero, C. and Rehman, T. (2003). Multiple Criteria Analysis for Agricultural Decisions, Elsevier, Amsterdam. Roy, A., Mackin, P., Wallenius, J., Corner, J., Keith, M., Schymik, G., and Arora, H. (2008). “An interactive search method based on user preferences,” Decision Analysis 5(4), 203–229. Roy, B. (1968). “La méthode ELECTRE,” Revue d’Informatique et de Recherche Opérationelle (RIRO) 8, 57–75. Roy, B. (1971). “Problems and methods with multiple objective functions,” Mathematical Programming 1(2), 239–266. Roy, B. (1978). “ELECTRE III: Un algorithme de classements fondé sur une représentation floue des préférences en présence de critères multiples,” Cahiers du Centre d’Etudes de Recherche Opérationnelle 20(1), 3–24. Roy, B. and Bertier, P. (1973). “La méthode ELECTRE II — Une Application au Média-planning,” in OR ’72, M. Ross (ed.), 291–302, North-Holland Publishing Company. Roy, B. and Vanderpooten, D. (1996). “The European school of MCDA: Emergence, basic features and current works,” Journal of Multi-Criteria Decision Analysis 5, 22–38. Roy, B. and Vincke, P. (1981). “Multicriteria analysis: Survey and new directions,” European Journal of Operational Research 8, 207–218. Roy, B., Vincke, Ph., and Brans, J.P. (1975). “Aide à la décision multicritère,” Revue Belge de Statistique 15(4), 23–53. Ruzika, S. and Wiecek, M.M. (2005). “Approximation methods in multiobjective programming,” Journal of Optimization Theory and Applications 126(3), 473–501. Saaty, T.L. (1977). “A scaling method for priorities in hierarchical structures,” Journal of Mathematical Psychology 15, 234–281. Saaty, T.L. (1977). “The Sudan transport study,” Interfaces 8(1), 37–57.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

178

Page 178

Multiple Criteria Decision Making

M. Köksalan, J. Wallenius and S. Zionts

Saaty, T.L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation, McGraw-Hill, New York. Saaty, T.L. (1986). “Axiomatic foundation of the analytic hierarchy process,” Management Science 32(7), 841–855. Saaty, T.L. (1996). Analytic Network Process: Decision Making with Dependence and Feedback, RWS Publications, Pittsburgh. Saaty, T. L. (1999). Decision Making for Leaders, RWS Publications, Pittsburgh. Saaty, T. and Gass, S. (1954). “Parametric objective function part I,” Operations Research 2, 316–319. Sakawa, M. (1983). “Interactive computer programs for fuzzy linear programming with multiple objectives,” International Journal of Man Machine Systems 5, 489–503. Sakawa, M. (1993). Fuzzy Sets and Interactive Multiobjective Optimization, Plenum, New York. Sakawa, M., Yano, H., and Yumine, T. (1987). “An interactive fuzzy satisficing method for multiobjective linear programming problems and its application,” IEEE Transactions on Systems, Man and Cybernetics 17(4), 654–661. Salminen, P., Korhonen, P., and Wallenius, J. (1989). “Testing the form of a decision-maker’s multiattribute value function based on pairwise preference information,” Journal of the Operational Research Society 40, 299–302. Salo, A. and Hämäläinen, R.P. (1992). “Preference assessment by imprecise ratio statements,” Operations Research 40(6), 1053–1061. Salukvadze, M.E. (1971). “Optimization of vector functionals I: The programming of optimal trajectories,” Automation and Remote Control 8, 1169–1178. Salukvadze, M.E. (1971). “Optimization of vector functionals II: The analytic construction of optimal controls,” Automation and Remote Control 9, 1347–1357. Salukvadze, M.E. (1972). “Linear programming problem with a vector-valued performance criterion,” Automation and Remote Control 33(6), 794–799. Samuelson, P.A. (1938). “A note on the pure theory of consumer’s behavior,” Economica 5(17), 61–71. Samuelson, P.A. (1948). “Consumption theory in terms of revealed preference,” Economica 15(60), 243–253.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

Page 179

Multiple Criteria Decision Making

References

179

Savage, L. (1954). The Foundations of Statistics, Wiley, New York. Sawaragi, Y., Nakayama, H., and Tanino, T. (1985). Theory of Multiobjective Optimization, Academic Press, Orlando. Sayin, S. (2003). “A procedure to find discrete representations of the efficient set with specified coverage errors,” Operations Research 51(3), 427–436. Schaffer, J.D. (1984). Some Experiments in Machine Learning Using Vector Evaluated Genetic Algorithms, Ph.D. thesis, Vanderbilt University, Nashville, TN. Sebenius, J. (1992). “Negotiation analysis: A characterization and review,” Management Science 38(1), 18–38. Sen, A.K. (1970). Collective Choice and Social Welfare, Holden Day, San Fransisco. Shakun, M. (1996). Negotiation Processes: Modeling Frameworks and Information Technology, Springer, Berlin. Shi, Y., Peng, Y., Kou, G., and Chen, Z. (2005). “Classifying credit card accounts for business intelligence and decision making: A multiple-criteria quadratic programming approach,” International Journal of Information Technology and Decision Making 4, 581–600. Shin, W.S. and Ravindran, A. (1992). “A comparative study of interactive tradeoff cutting plane methods for MOMP,” European Journal of Operational Research 56, 380–393. Simon, H. (1955). “A behavioral model of rational choice,” Quarterly Journal of Economics 69, 99–118. Simon, H. (1996). Models of My Life, MIT Press, Cambridge, MA. Słowiński, R. (1992). Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory, Kluwer Publishers, Dordrecht. Soylu, B. and Köksalan, M. (2010). “A favorable weight based evolutionary algorithm for multiple criteria problems,” IEEE Transactions on Evolutionary Computation 14(2), 191–205. Spronk, J. (1981). Interactive Multiple Goal Programming: Applications to Financial Planning, Martinus Nijhoff Publishing, Boston. Spronk, J., Steuer, R.E., and Zopounidis, C. (2005). “Multicriteria Decision Aid/ Analysis in Finance,” in Multiple Criteria Decision Analysis: State of The Art Surveys, Figuera, J., Greco, S., Ehrgott, M. (Eds.), 799–857, Springer, Berlin.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

180

Page 180

Multiple Criteria Decision Making

M. Köksalan, J. Wallenius and S. Zionts

Srinivas, N. and Deb, K. (1994). “Multiobjective optimization using nondominated sorting in genetic algorithms,” Evolutionary Computing Journal 2, 221–248. Srinivasan, V. and Shocker, A.D. (1973a). “LP techniques for multidimensional analysis of preferences,” Psychometrica 38, 337–369. Srinivasan, V. and Shocker, A.D. (1973b). “Estimating the weights for multiple attributes in a composite criterion using pairwise judgments,” Psychometrica 38, 473–493. Stancu-Minasian, I.M. (1975). “A Selected Bibliography of Works Related to the Multiple Criteria Problem Decision Making,” Academy of Economic Studies, Department of Economic Cybernetics, Bucharest, Romania. Steuer, R.E. (1976). “Multiple objective linear programming with interval criterion weights,” Management Science 23(3), 305–316. Steuer, R.E. (1986). Multiple Criteria Optimization: Theory, Computation and Application, Wiley, New York. Steuer, R.E. and Choo, E.-U. (1983). “An interactive weighted Tchebycheff procedure for multiple objective programming,” Mathematical Programming 26(3), 326–344. Steuer, R.E. and Na, P. (2003). “Multiple criteria decision making combined with finance: A categorized bibliography,” European Journal of Operational Research 150(3), 496–515. Steuer, R.E., Qi, Y., and Hirschberger, M. (2007). “Suitable-portfolio investors, nondominated frontier sensitivity, and the effect on standard portfolio selection,” Annals of Operations Research 152, 297–317. Stewart, T.J. (1976). Bayes Optimal Experimental Design for Determination of a Response Surface Maximum, Ph.D. thesis, University of Cape Town. Stewart, T.J. (1992). “A critical survey on the status of multiple criteria decision making theory and practice,” OMEGA: International Journal of Management Science 20, 569–586. Stewart, T.J. (1993). “Use of piecewise linear value functions in interactive multicriteria decision support: A Monte Carlo study,” Management Science 39, 1369–1381. Stewart, T.J. and Scott, L. (1995). “A scenario-based framework for multicriteria decision analysis in water resources planning,” Water Resources Research 31, 2835–2843.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

Page 181

Multiple Criteria Decision Making

References

181

T’Kindt, V. and Billaut, J.-C. (2001). “Multicriteria scheduling problems: A survey,” RAIRO Operation Research 35, 143–163. Teich, J. (1991). Decision Support for Negotiations, Ph.D. thesis, SUNY Buffalo, School of Management. Teich, J., Wallenius, H., and Wallenius, J. (1999). “Multiple issue auction and market algorithms for the World Wide Web,” Decision Support Systems 26(1), 49–66. Teich, J., Wallenius, H., Wallenius, J., and Zionts, S. (1996). “Identifying Paretooptimal settlements for two-party resource allocation negotiations,” European Journal of Operational Research 93, 536–549. Thiele, L., Miettinen, K., Korhonen, P., and Molina, J. (2009). “A preferencebased interactive evolutionary algorithm for multiobjective optimization,” Evolutionary Computation 17(3), 411–436. Thiriez, H. and Zionts, S. (Eds.) (1976). “Multiple Criteria Decision Making,” Proceedings, May 1975, Jouy-en-Josas, France, Number 130. Lecture Notes in Economics and Mathematical Systems: Operations Research, Springer-Verlag, Berlin. Torrance, G.W., Feeny, D.H., Furlong, W.J., Barr, R.D., Zhang, Y.M., and Wang, Q.N. (1996). “Multi-attribute utility function for a comprehensive health status classification system: Health utilities index mark II,” Medical Care 34(7), 702–722. Torrance, G.W., Furlong, W., Feeny, D., and Boyle, M. (1995). “Multi-attribute preference functions — Health utilities index,” Pharmaco Economics 7(6), 503–519. Tversky, A. and Kahneman, D. (1991). “Loss aversion in riskless choice,” Quarterly Journal of Economics 106(4), 1039–1061. Ulungu, E.L. and Teghem, J. (1994). “Multi-objective combinatorial optimization problems: A survey,” Journal of Multiple Criteria Decision Analysis 3(2), 83–104. Van Wassenhove, L.N. and Gelders, F. (1980). “Solving a bicriterion scheduling problem,” European Journal of Operational Research 4, 42–48. Villarreal, B. and Karwan, M.H. (1981). “Multi-criteria integer programming: A (hybrid) dynamic programming recursive approach,” Mathematical Programming 21, 204–223. Vincke, Ph. (1992). Multicriteria Decision-Aid, Wiley, Chichester.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

182

Page 182

Multiple Criteria Decision Making

M. Köksalan, J. Wallenius and S. Zionts

von Neumann, J. and Morgenstern, O. (1944). Theory of Games and Economic Behavior, Princeton University Press, Princeton, NJ. von Winterfeldt, D. and Edwards, W. (1986). Decision Analysis and Behavioral Research, Cambridge University Press, Cambridge, England. von Winterfeldt, D. and Schweitzer, E. (1998). “An assessment of tritium supply alternatives in support of the U.S. nuclear weapons stockpile,” Interfaces 22, 92–118. Wallenius, J. (1975). Interactive Multiple Criteria Decision Methods: An Investigation and an Approach, Ph.D. thesis, A-14, Helsinki School of Economics. Wallenius, J. (1975). “Comparative evaluation of some interactive approaches to multicriterion optimization,” Management Science 21, 1387–1396. Wallenius, J., Dyer, J., Fishburn, P., Steuer, R., Zionts, S., and Deb, K. (2008). “Multiple criteria decision making/multiattribute utility theory: Recent accomplishments and what lies ahead,” Management Science 54(7), 1336–1349. Wang, J.G. and Zionts, S. (2005). “WebAIM: An online aspiration-level interactive method,” Journal of Multi-Criteria Decision Analysis 13, 51–63. Wang, J.G. and Zionts, S. (2008). “Negotiating wisely: Considerations based on multi-criteria decision making/multi-attribute utility theory,” European Journal of Operational Research 188(1), 191–205. Weber, M. (1987). “Decision making with incomplete information,” European Journal of Operational Research 28(1), 44–57. Wierzbicki, A. (1964). Nonlinear Dynamics in Control, Ph.D. thesis, Warsaw University of Technology. Wierzbicki, A. (1975). “Penalty Methods in Solving Optimization Problems with Vector Performance Criteria,” in Proceedings of 6th IFAC World Congress, Cambridge, Boston. Wierzbicki, A. (1977). “Basic properties of scalarizing functionals for multiobjective optimization,” Mathematische Operationsforschung und Statistik 8(1), 55–60. Wierzbicki, A. (1980). “The Use of Reference Objectives in Multiobjective Optimization,” in Multiple Criteria Decision Making: Theory and Application, Lecture Notes in Economics and Mathematical Systems 177, Fandel, G. and Gal, T. (Eds.), 468–486, Springer, Berlin. Wierzbicki, A. and Nakamori, Y. (2006). Creative Space: Models of Creative Processes, Springer, Berlin.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

Page 183

Multiple Criteria Decision Making

References

183

Wilkie, W.L. and Pessemier, E.A. (1973). “Issues in marketing’s use of multiattribute attitude models,” Journal of Marketing Research 10(4), 428–441. Wu, H., Tzeng, G., and Chen, Y. (2009). “A fuzzy MCDM approach for evaluating banking performance based on balanced scorecard,” Expert Systems with Applications 36(6), 10135–10147. Yager, R.R. (1982a). “Multiple criteria decisions with soft information: An application of fuzzy set and possibility theory-part I,” Journal of Fuzzy Mathematics 2, 21–28. Yager, R.R. (1982b). “Multiple criteria decisions with soft information: An application of fuzzy sets and possibility theory-part II,” Journal of Fuzzy Mathematics 3, 7–16. Yager, R.R. (1988). “On ordered weighted averaging aggregation operators in multi-criteria decision making,” IEEE Transactions on Systems, Man and Cybernetics 18, 183–190. Yu, P.L. (1980). “Behavior bases and habitual domain of human decision/ behavior-concepts and applications,” Lecture Notes in Economics and Mathematical Systems 177, Springer, Berlin, 511–539. Yu, P.L. (1985). Multiple Criteria Decision Making: Concepts Techniques and Extensions, Plenum, New York. Yu, P.L. (1990). Forming Winning Strategies: An Integrated Theory of Habitual Domains, Springer, Berlin. Yu, P.L. and Leitmann, G. (1974). “Compromise solutions, domination structures and Salukvadze’s solution,” Journal of Optimization Theory and Applications 13(3), 362–378. Yu, P.L. and Zeleny, M. (1975). “The set of all non-dominated solutions in linear cases and a multicriteria simplex method,” Journal of Mathematical Analysis and Applications 49(2), 430–468. Yu, P.L. and Zeleny, M. (1976). “Linear multiparametric programming by multicriteria simplex method,” Management Science 23(2), 159–170. Zadeh, L.A. (1963). “Optimality and non-scalar-valued performance criteria,” IEEE Transactions on Automatic Control AC-8(1), 59–60. Zadeh, L.A. (1965). “Fuzzy sets,” Information and Control 8, 338–353. Zeleny, M. (1974). “A concept of compromise solutions and the method of the displaced ideal,” Computers and Operations Research 1(3), 479–496. Zeleny, M. (1982). Multiple Criteria Decision Making, McGraw-Hill, New York. Zeleny, M. (2005). Human Systems Management, World Scientific, Singapore.

b1148_References.qxd

5/5/2011

6:31 AM

b1148

184

Page 184

Multiple Criteria Decision Making

M. Köksalan, J. Wallenius and S. Zionts

Zimmermann, H.J. (1978). “Fuzzy programming and linear programming with several objective functions,” Fuzzy Sets and Systems 1, 45–55. Zionts, S. (1965). Reduction Techniques of Linear Programming and Their Application, Ph.D. Dissertation, Carnegie Institute of Technology, Pittsburgh, PA. Zionts, S. (1967). “A bargaining model for allocating steel production,” CORSI Bulletin (Operations Research Society of India), 69–78. Zionts, S. (1979). “MCDM — If not a Roman numeral, then what?” Interfaces 9, 94–101. Zionts, S. (1981). “A multiple criteria method for choosing among discrete alternatives,” European Journal of Operational Research 7, 143–147. Zionts, S. and Wallenius, J. (1976). “An interactive programming method for solving the multiple criteria problem,” Management Science 22, 652–663. Zionts, S. and Wallenius, J. (1980). “Identifying efficient vectors: Some theory and computational results,” Operations Research 28, 785–793. Zionts, S. and Wallenius, J. (1983). “An interactive multiple objective linear programming method for a class of underlying nonlinear utility functions,” Management Science 29, 519–529. Zitzler, E. (1999). Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications, Ph.D. thesis, ETH Zurich, Switzerland. Zitzler, E., Laumanns, M., and Thiele, L. (2002). “SPEA2: Improving the Strength Pareto Evolutionary Algorithm,” in EUROGEN 2001, Evolutionary Methods for Design, Optimization and Control with Applications to Industrial Problems, Giannakoglou, K., Tsahalis, D., Periaux, J., Papailou, P., and Fogarty, T. (Eds.), 95–100, Athens, Greece. Zopounidis, C. and Doumpos, M. (2002). “Multicriteria classification and sorting methods: A literature review,” European Journal of Operational Research 138, 229–246. Zoutendijk, G. (1960). Methods of Feasible Directions, Elsevier, Amsterdam.

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certainty 23, 27 classification 47, 55, 56 compromise solution 18, 21, 144 computer graphics 17, 35–38, 44 concordance 57 conjoint analysis 10, 27 consumer behavior 6 continuous-solution-space 34 contract curve 4 convex cone 37 criterion 16, 36, 37, 45, 56, 64, 84

achievement scalarizing function 17, 18, 25, 26, 35, 148 ADBASE 20, 141 additive 27, 39, 41, 51, 57 adjacent 23, 37 aggregation 3, 8, 40, 99 agriculture 35 aircraft design 53 analytic hierarchy process (AHP) 17, 26, 31, 41, 47, 48, 135, 158 analytic network process (ANP) 48 approval voting 9 Arrow’s paradox 8 artificial intelligence 7, 16, 123 aspiration level 8, 142 assignment 55, 58 attribute 4, 23, 25, 53, 55 auction reverse 52

data envelopment analysis (DEA) 27, 35, 44, 51, 75, 101, 104, 122 decision analysis 1, 4, 10, 15, 23, 24, 31, 46, 81, 96, 97, 106, 108, 115, 118, 119, 123–127, 138, 142, 143, 149, 150 decision rule 47, 77 decision support 26, 35, 38, 43, 45, 48–50, 55, 66, 67, 70, 74, 81, 115, 122, 124–127, 137, 146, 148, 158 decision theory 7, 9, 10, 158 decision tree 10, 131 decomposition 18, 19, 21, 112 descriptive 8, 28, 46

bargaining 4, 15, 50, 154, 157 behavioral decision theory 7 bibliometric 54 bi-criteria 15, 55, 56, 58 branch-and-bound 39 chemical process optimization 53 185

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discordance 57 discrete 8, 34, 36–38, 95, 120, 143 displaced ideal 21, 153 domination structures 63 dummy 37 economics 2–10, 13, 22, 28, 35, 42, 45, 51, 54, 55, 57, 63, 85, 95, 101, 103, 105, 109, 120, 122, 123, 126–128, 131–133, 139, 144, 146, 147, 151–153, 155, 157 e-Commerce 44, 52 ε-MOEA 59 Edgeworth box 3, 4 efficiency proper 15, 98 efficient frontier 15, 25, 51, 75 vector 13, 15 ELECTRE 11, 17, 18, 57, 134 ELECTRE-TRI 11 energy 35, 53, 54, 78, 102, 107, 108, 111, 115, 117, 118, 143, 144 Euclidean distance 20 even swap 47, 74 evolutionary multiobjective optimization (EMO) 44, 45, 53, 58, 59, 60, 76, 77, 79, 84, 85, 105, 128, 146, 157, 158 expected utility theory 4, 5 EXPERT CHOICE 26, 48 extreme point 20, 21, 23, 45, 63, 98 financial modeling 35 forest management 53 French School 11, 18, 31, 84, 158

function concave 21 quasiconcave 37 fuzzy logic 16, 41 fuzzy set theory 16, 35, 40, 144 FWEA 59 games 4, 5, 9, 107, 115, 130, 136, 150, 151 game theory 30, 115, 130, 150, 153 genetic algorithm 42, 44, 45, 56, 104, 136 goal programming 14, 15, 25, 31, 32, 42, 85, 100, 104, 132, 158 gradient 19 group decision making 25, 35, 49, 51, 63, 115, 151 habitual domain 28–30, 151 Health Utilities Index 54 heuristic 55, 56, 57, 58 hierarchy 17, 26, 31, 47, 48, 135, 158 hub location 58 hybrid 45, 85, 146 hypertext 48 ideal point 20 solution 18 impossibility theorem 8, 25 inconsistency 26 independence 8, 48, 96 indifference curve 3, 6, 37 information technology 50, 75, 136, 137

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integer programming 15, 39, 95, 111, 112, 117, 155 interactive 17, 19–21, 23, 25, 31, 32, 34–39, 41, 45, 49, 54, 59, 64, 66, 67, 81, 96, 120, 122, 123, 125, 127, 136, 142, 146, 158 interval scale 27 knapsack 55, 58 knowledge discovery 46 lambda problem 23 lexicographic 14, 25 linear programming 11, 12, 14, 18, 21, 23, 27, 40, 42, 44, 45, 51, 64, 97, 98, 100, 110, 123, 141, 145, 152, 154 location 58, 102, 144 loss aversion 27 majority 1, 8, 25, 60 man-machine 19 mathematical programming 1, 11–13, 15, 17, 20, 23, 31, 32, 85, 98 medical decision making 54, 127 mental model 45 method of standard gambles 4 MINIMAX 18 moral algebra 2, 47 most preferred solution 36, 37, 39, 50–52 multiattribute 17, 23–25, 27, 39, 52, 54, 55, 63, 108, 119, 158 multidimensional scaling 63

187

multiobjective combinatorial optimization (MOCO) 44, 55–58, 77, 120 genetic algorithm 42, 44 multiple criteria decision aid 17, 66, 83, 86, 133 multiple criteria decision making 1, 2, 4, 17, 18, 31, 32, 41, 47, 51, 63, 64, 66, 74, 84, 86, 89, 93, 102, 104, 107, 110, 114, 116–118, 120, 122–129, 131, 132, 134–138, 140, 142–145, 147, 148, 150–152, 155, 157 multiple objective linear programming 14, 21, 23, 44, 45, 51, 64, 98, 141 mathematical programming 1, 11–13, 15, 17, 23, 31, 32, 142, 158 multiple-response design 54 multiplicative 27, 55 NEGOPLAN 50 negotiation 4, 15, 35, 44, 49–51, 74, 127, 131, 146, 148, 155 neoclassical economics 2, 6 network flow 55 noncompensatory 57 nondominated sorting genetic algorithm 44 nonlinear programming 12, 98 nonradial 51 norm 25 normalized weight 18

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normative 8, 28, 46 NP-hard 58 NSGA-II 59 objective 1, 11–15, 18, 20, 21, 23, 26, 32, 42, 44, 45, 51, 54, 58, 64, 66, 84, 85, 98, 111, 120, 135, 141, 146, 157, 158 online 48, 49, 52, 158 operations research 10, 11, 14, 15, 21, 23, 27, 39–41, 63, 85, 95, 96, 98, 101, 103, 106, 109–112, 116–120, 122, 127–129, 131, 133–135, 138, 142–144, 149–151, 154 optimal control 15, 16, 20, 25, 30, 115, 135, 151 optimization 2, 17, 21, 25, 26, 31, 41, 44, 45, 49, 53, 55–58, 60, 64, 66, 67, 75–77, 79, 81, 84, 85, 95, 98, 105, 112, 120, 125, 127–129, 135, 136, 147, 148, 150, 151, 157, 158 ordered weighted averaging (OWA) operators 40 ordinal 8, 57 outranking relation 18, 41, 57, 63, 64, 134, 145 pairwise 39, 48 parametric objective function 14 Pareto efficiency 3, 8, 15, 23, 27, 51, 52, 75, 98, 104, 122, 157 genetic algorithm 42, 44, 45, 56, 104, 136

optimality 3, 15, 101, 152, 157 pareto race 36, 67, 68, 122 polyhedron 21, 23, 98 portfolio optimization 60 pre-emptive 14 preference function 10 modeling 46, 99, 126, 137, 145, 157 problem structuring 45, 46, 96 projection 20, 51 PROMETHEE 41 prospect theory 27, 108 radiation therapy 53 RAMONA 50 ranking 1, 8, 11, 39, 42, 45 ratio scale 26 rational man 7 rationality limited 8 bounded 8 reachable set method 20 reference direction 42, 122 point 25, 27 regret 40, 95, 96 resource allocation 13, 110, 117 revealed preference 6 revised simplex algorithm 20 risk 39, 48, 57, 60, 74, 84, 95, 96, 106, 107, 114, 115, 118, 149 river basin development 53 robustness analysis 16 rough set 46, 47, 57, 126, 138

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scheduling 55, 56, 58, 98, 133, 144 SCOOP 11 scoring model 43, 53 set theory 2, 16, 35, 40, 126, 138, 144 shopping agent 52, 53 shortest path 55, 58 simplex algorithm 11, 12, 20 SMART 24, 25, 47, 108, 131 social choice 8, 11, 25, 109 sorting 11, 44, 56, 57 spanning tree 55, 58 SPEA2 59 spreadsheet 43, 48, 158 statistical decision theory 10 STEP-method 18, 123 stochastic optimization 81 supported 1, 36, 55, 58 surrogate worth trade-off method 26 target 14, 36 Tchebycheff 35 trade-off 19, 23, 26, 27, 35, 36, 47, 114, 131, 153, 157 trajectory 20 traveling salesperson 58 uncertainty 11, 23, 96, 111, 137 unstructured 46 unsupported 58 UTA 41 UTADIS 57

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utility assessment 6, 32 function elicitation 10 theory 1, 3–5, 11, 17, 24, 25, 27, 39, 54, 96, 99, 108, 119, 158 value function measurable multiattribute 27 value Focused Thinking 24, 45, 46, 119 value theory 5, 11, 109 vector maximization 15, 110, 141 optimization 17, 148, 158 vector valued 15, 16 VEGA 42 verbal decision analysis 46, 124 VIG 68 VIMDA 38 VISA 39 visualization 37, 38, 125 water regulation 53 water resource management 26, 102 weighted sum 11, 16, 58 win-win 50 WorldScan 33, 34, 141 World Wide Web 43, 48, 53 WWW-NIMBUS 49 Zionts-Wallenius method 17, 23, 35–37, 50, 57, 74, 84

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Bod, P. 152 Bodily, S. 65 Borda, J.-C. 1 Bouyssou, D. 18, 57, 99, 134 Boyle, M. 167 Bragge, J. 54 Brams, S. 9, 109 Branke, J., 59, 85 Brans, J.P. 18, 41, 84 Brown, R. 124, 140, 141 Buffa, E. 106 Bultez, A. 66 Busemeyer, J.R. 108 Bushenkov, V. 20, 37

Ackoff, R.L. 6 Afriat, S. 6 Agarwal, S. 165 Airo, S. 45, 58 Aksoy, Y. 31, 69, 99 Aneja, Y.P. 55 Arbel, A. 41 Arora, H. 177 Arrow, K. 8, 9, 25 Assad, A.A. viii, 168 Azizoglu, M. 56, 73 Balibek, E. 60, 121 Barr, R.D. 181 Bell, D. 40, 65, 66, 81, 95, 109, 118, 129 Belton, V. 39, 46, 51, 57, 66, 74, 76, 85, 93, 94, 96, 97, 142 Benayoun, R. 17, 18 Benson, H.P. 56, 76, 93, 97 Berezovsky, B. 67 Berge, C. 133 Berners-Lee, T. 48 Bertier, P. 18, 133 Bichler, M. 53 Billaut, J.-C. 58 Bitran, G. 39, 66

Cantor, G. 2, 70, 76, 90, 93, 97, 99 Captivo, M.E. 58 Carlsson, C. 40 Cattolico, M. 165 Chankong, N. 31, 66, 114 Charnes, A. 14, 15, 27, 35, 46, 51, 100, 101, 103, 104 Chen, Y. 61 Chen, Z. 176 Choo, E.-U. 35 Churchman, C.W. 6, 63 Climaco, J. 55, 58, 70 191

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Cochrane, J.L. 63, 64, 152 Coello, C.A.C. 53, 59, 60, 84 Cohon, J.L. 17, 26, 55, 66, 68, 73, 74, 93, 101, 102, 141 Condorcet, N. 1, 2 Contini, B. 15, 21, 154, 157 Cooper, W.W. 14, 15, 27, 35, 46, 51, 93, 100, 101, 103, 104, 154 Corne, D. 84 Corner, J. 177 Costa, M.G. 42, 58, 83 Cray, D. 171 Da Cunha, N.O. 16 Dantzig, G.B. 11, 12, 95, 135 Dauer, J.P. 56 Dawes, R. 63 Deb, K. 44, 45, 59, 60, 76, 84, 85, 93, 104, 146 Debreu, G. 5, 6 Dejax, P. 58 de Montgolfier, J. 18 de Neufville, R. 24 Diepenhorst, A. 139 Doğrusoz, H. 120 Doumpos, M. 57 Doyle, R.H. 51 Drake, A.W. 165 Duckstein, L. 31, 66 Dyer, J.S. 17–19, 23, 27, 31, 32, 63, 65, 79, 81, 93, 105–107 Dyson, R.G. 51 Ecker, J. 66 Edgeworth, F. 2–4, 70, 76, 93, 102, 105, 106, 116, 125, 129, 138, 144, 147, 150

Edwards, W. 7, 24, 25, 31, 81, 107, 108, 149, 158, 159 Ehrgott, M. 58, 78 Ehtamo, H. 50 Einhorn, H. 65 Eppel, T. 39 Erdös, P. 109 Evans, G.W. 31, 32, 141 Evans, J. 20, 141 Fandel, G. 21, 64, 65, 71, 110 Farquhar, P.H. 31, 32, 65 Feeny, D. 54 Feillet, D. 58 Feinberg, A. 17, 18, 19, 23 Ferguson, R.O. 14, 104 Figuera, J. 175 Fishburn, P.C. 9, 11, 25, 63, 65, 81, 108, 109, 158 Fleming, P. 44 Fogarty, T. 184 Fonseca, C. 44, 45, 84 Forman, E. 26, 41 Franklin, B. 1, 2, 47 Franz, L. 66, 107 Friedman, H. 26 Frisch, R. 10 Furlong, W. 54 Gal, T. 21, 65, 71, 93, 110, 141 Gallagher, R.J. 56 Gandibleux, X. 58, 84 Gass, S. 12–14, 26 Gehring, H. 110 Gelders, F. 56 Gendreau, M. 58

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Geoffrion, A.M. 15, 17, 18, 19, 23, 106, 111, 112 Giannakoglou, K. 184 Gluckaufova, D. 141 Goicoechea, A. 31, 68 Goldberg, D. 44, 45 Grauer, M. 66, 81, 141 Greco, S. 46, 57, 85, 126, 138 Green, J.R. 51 Green, P. 27, 63 Guttman, R. 53 Haimes, Y. 26, 31, 65, 66, 71, 79, 93, 113, 114 Hall, W. 26 Hallerbach, W.G. 61 Halme, M. 51 Hämäläinen, R.P. 16, 35, 41, 49, 50, 76, 93, 115, 116 Hammond, J.S. 47, 131 Hanne, T. 50, 66, 73, 82, 147 Hansen, D.R. 31 Hansen, P. 64, 66, 83 Harker, P.T. 41 Henig, M. 55, 66 Hirschberger, M. 60 Hobbs, B.F. 35, 53 Hogoveen, J.A. 56 Hokkanen, J. 53 Honko, J. 22, 147 Hora, S. 54 Horn, J. 44 Howard, R. 9, 10, 17, 23, 35, 39, 46, 47, 49, 74, 81, 90, 93, 95, 96, 119, 129–131, 149 Hsieh, T-Y. 41

193

Hsu, C. 174 Huang, J. 174 Ignizio, J. 42, 63 Ijiri, Y. 15, 63 Isaacs, R. 150 Isermann, H. 21, 63, 141 Ishibuchi, H. 56 Islei, G. 67 Jacquet-Lagreze, E. 41, 57 Jahn, J. 66 Jones, D. 86, 100 Joro, T. 51 Kahneman, D. 27, 28, 57, 108 Kamenev, G. 38 Kantorovich, L. 12, 123 Karahan, I. 59, 60 Karasakal, E. K. 56, 73, 121 Karlin, S. 165 Karpak, B. 84, 141 Karwan, M.H. 37, 39, 71, 116, 120, 155 Keefer, D. 65 Keeney, R. 17, 23, 24, 39, 45–47, 50, 51, 63–65, 74, 81, 93, 96, 118, 119, 129, 131, 149 Keith, M. 177 Kersten, G. 50, 81, 82, 127 Kettunen, E. 50 Keuneran, D. 162 Kimball, G.E. 9, 112 Kirkwood, C.W. 39, 43, 50, 65 Klinger, A. 16

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Köksalan, M. 36, 37, 39, 40, 54, 56–60, 68, 69, 73, 74, 77, 80, 82, 84, 93, 117, 119 Kondakci, S. 56, 73, 82 Koo, A.Y.C 6 Koopmans, T.C. 13 Koperczak, Z. 171, 175 Korhonen, P. 27, 35–40, 42, 45, 50–52, 57, 59, 66–69, 71, 74, 75, 81, 85, 89, 93, 94, 121, 122, 141, 146 Kornbluth, J. 21, 29, 141 Kou, G. 176 Kuhn, H.W. 12, 13 Kumar, A. 59 Kurzhanski, A. 81 Laakso, J. 35, 36, 42, 122 Lahdelma, R. 53 Lamont, G.B. 53, 60 Larichev, O. 16, 18, 46, 54, 57, 71, 74, 82, 93, 123, 159 Laumanns, M. 59 Lee, I. 171 Lee, S. 15, 42, 65 Lee, W. 60, 175 Leitmann, G. 20 Lewandowski, A. 81 Lieberman, E. 20, 31, 32 Lieberman, G.J. 111 Lockett, G. 67, 141 Lokman, B. 56 Loomes, G. 40 Lootsma, F. 81, 82 Lotfi, V. 15, 16, 36, 40, 63, 68, 117, 142

Lotov, A. 20, 37, 38, 82, 93, 124, 125, 141 Lu, S.-T. 170 Luce, R.D. 9, 10, 81, 130 Luptacik, M. 75 MacCrimmon, K. 63 Mackin, P. 177 Maes, P. 53 Mäkelä, M.M. 49 Makowski, M. 83 Malakooti, B. 37 Marchant, T. 57 Mareschal, B. 41 Marks, D.H. 26, 101 Marschak, J. 106 Matarazzo, B. 46, 57, 86, 93, 116, 126, 138 Matheson, J.E. 10 Matwin, S. 50 Meier, P. 53 Merkhofer, M. 39 Mesarovic, M.D. 14, 15 Meyarivan, T. 165 Michalowski, W. 50, 55, 66, 81, 82, 126, 127 Miettinen, K. 49, 82, 85, 94, 128, 146 Miles, R.F., Jr. 24, 105, 118, 133, 141 Mohan, M. 59 Molina, J. 181 Mishra, S. 59 Morgenstern, O. 4, 5, 10 Morin, T.L. 82, 98 Morse, J. 66

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Morse, P.M. 165 Moshkovich, H. 46, 57 Moskowitz, H. 27, 29, 71 Mosteller, C.F. 107 Moukas, A.G. 53 Mousseau, V. 57, 86 Murata, T. 56 Na, P. 61 Nafploitis, N. 44 Nair, K.P.K. 55 Nakamori, Y. 148 Nakayama, H. 31, 35, 60, 66, 67, 81, 90, 93, 129 Näslund, B. 22, 146 Nedoma, J. 21 Newell, A. 7 Nickel, S. 58 Nijkamp, P. 139 Olson, D. 37, 54 Opricovic, S. 41, 144 Ozernoy, V.M. 20, 31, 32, 66 Özpeynirci, Ö. 57, 58, 121 Papailou, P. 184 Pardalos, P.M. 171 Pareto, V. 3, 4, 8, 13, 16, 36, 38, 44, 58, 59, 67, 68, 70, 76, 93, 102, 105, 106, 116, 122, 125, 129, 138, 144, 147, 150, 157, 158 Passy, U. 63 Pawlak, Z. 47, 138 Peng, Y. 60 Perehkod, I. 141 Periaux, J. 184

195

Perny, P. 162 Phelps, S.P. 59, 121 Phillips, L.D. 24, 107, 108 Pirlot, M. 18, 57 Plante, R.D. 54 Polak, E. 16 Pospelova, I. 38, 125 Pöyhönen, M. 49 Pratap, A. 165 Priestly, J. 1 Puerto, J. 58 Qi, Y. 60 Raiffa, H. 9, 10, 17, 23, 24, 35, 39, 46, 47, 49, 50, 74, 81, 90, 93, 95, 96, 119, 129–131, 149 Raith, A. 58 Ramesh, R. 39, 117 Ramsey, F.P. 4, 5, 96, 106, 109, 119, 131, 149 Ravindran, A. 31, 32 Rehman, T. 35, 42 Rhodes, E. 27, 35, 51, 104 Rodríguez-Chía, A.M. 58 Romero, C. 31, 32, 35, 42, 93, 132 Ross, M. 177 Roubens, M. 18, 66 Roy, A. 23, 140 Roy, B. 11, 17, 18, 31, 57, 63–66, 81, 83, 93, 99, 132–134, 137 Ruiz, F. 141 Ruzika, S. 56 Saarinen, E. 116

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Saaty, T.L. 14, 17, 26, 31, 41, 47, 48, 66, 93, 134, 135 Sagala, P.N.S. 37, 39, 121 Sakawa, M. 16, 40, 41, 93, 135, 136 Salminen, P. 39, 53 Salo, A. 41 Salo, S. 51 Salukvadze, M.E. 20 Samuelson, P.A. 6 Sarin, R. 27, 39, 65 Savage, L. 4, 108 Sawaragi, Y. 31, 35, 67, 81, 90, 129 Sayin, S. 56, 73, 85, 99 Schaffer, J.D. 42, 44 Schlaifer, R. 10 Schoemaker, P. 66 Schweitzer, E. 54 Schymik, G. 177 Scott, L. 54, 103 Sebenius, J. 51 Sen, A. 8, 9 Shakun, M. 50 Shi, Y. 60, 75, 79, 80, 93, 136, 137, 141 Shin, W.S. 31, 32 Simon, H. 7, 8, 14, 103, 159 Siskos, J. 41, 83 Słowiński, R. 47, 57, 77, 83, 85, 93, 137, 138 Soismaa, M. 82 Soland, R. 68 Soylu, B. 58, 59, 121 Spronk, J. 31, 32, 35, 61, 66, 67, 71, 72, 84, 93, 138–141, 155 Srinivas, N. 44, 117 Stanchev, I. 141

Stancu-Minasian, I.M. 20 Stephenson, M. 66 Steuer, R.E. 17, 20, 21, 31–35, 52, 60, 61, 63–65, 69, 73, 75, 84, 85, 93, 94, 123, 140, 152 Stewart, T.J. 31, 35, 37, 46, 54, 57, 71, 74, 77, 85, 93, 94, 142, 143 Sugden, R. 40 Sun, E. 56, 99 Sundar, J. 59 Suppes, P. 165 Szpakowicz, S. 175 Tamiz, M. 86 Tanino, T. 31 Teich, J. 50, 53, 82 Teghem, J. 18, 55, 147 Tell, B. 65 Tergny, J. 18 Thanassoulis, E. 51 Thiele, L. 59, 60, 84 Thiriez, H. 63, 89, 155 Thompson, G.L. 154 T’Kindt, V. 58 Topchisvili, A. 141 Torrance, G.W. 54 Tsahalis, D. 184 Trzaskalik, T. 141 Tucker, A.W. 12, 13 Tukey, J.W. 10 Tversky, A. 27, 28, 57, 81, 84, 108 Tzeng, G. 41, 60, 61, 68, 73, 78, 93, 143, 144, 150 Ulu, C. 57 Ulungu, E.L. 55

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Vanderpooten, D. 31 Van Wassenhove, L.N. 56 Vargas, L.G. 41 Veldhuizen, D.A.V. 60 Vetschera, R. 50, 75 Vickers, S.P. 39 Villarreal, B. 117 Vincke, Ph. 18, 31, 41, 64, 93, 144 Von Neumann, J. 4, 5, 10, 25, 101, 109 Von Winterfeldt, D. 24, 31, 39, 54, 81, 93, 107, 108, 148, 149 Wagner, H. 111 Wallenius, H. 50, 53, 73 Wallenius, J. 17, 21–23, 27, 35–37, 39, 43, 45, 48, 50–53, 57, 59, 61, 64–66, 68, 71–74, 81, 82, 84, 85, 93, 94, 115, 122, 128, 145–147, 155 Wallenius, M. 145 Walras, L. 3 Wang, J.G. 49, 51 Wang, Q.N. 181 Wang, S. 79 Weber, M. 40, 66 Wedley, W. 76 Wehrung, D. 65

197

Wiecek, M.M. 56 Wierzbicki, A. 16–18, 25, 35, 66, 67, 70, 81, 85, 89, 93, 147, 148 Wilhelm, J. 64 Wood, E. 141 Wu, H. 61 Yager, R.R. 40 Yano, H. 178 Yoon, M. 60 Yu, P.L. 16, 17, 20, 21, 28, 29, 30, 31, 57, 63, 66, 68, 70, 71, 75, 79, 80, 93, 136, 150, 151, 152 Yumine, T. 178 Yun, Y. 60 Zadeh, L.A. 15, 16, 40, 63 Zeleny, M. 17, 21, 29, 31, 63–65, 69, 70, 75, 79, 93, 141, 151, 152 Zhang, Y.M. 181 Zielniewicz, P. 163 Zimmermann, H. J. 40 Zionts, S. 15, 17, 21–23, 32, 33, 35–37, 39, 46, 49–51, 57, 63–67, 69–72, 74, 79–81, 84, 93, 94, 117, 120, 141, 142, 146, 153–157 Zitzler, E. 45, 59, 84 Zopounidis, C. 57, 61, 77, 83 Zoutendijk, G. 12

"Our ability to analyze and resolve complex decision problems is one of the most important developments of the last half of the 20th century. But, like all such endeavors, advances were often based on earlier ideas from a multitude of fields, ideas that encouraged and gave impetus to new generations of researchers. All readers of Multiple Criteria Decision Making: From Early History to the 21st Century will find that the authors have woven the early and modern histories of MCDM into a scientific adventure story, one that helps us to understand better how advances in a field of research are the result of many, many seemingly unrelated activities." Professor Emeritus Department of Decision, Operations and Information Technologies Robert H. Smith School of Business, University of Maryland, College Park

"Rarely do we get to understand the evolution of a scientific field told with such care and understanding. And a handy guide to the MCDM literature as well! I'll have all of my students read it!"

Mark H. Karwan Praxair Professor in Operations Research, SUNY Distinguished Teaching Professor Industrial and Systems Engineering at the University at Buffalo (SUNY)

"I really enjoyed reading this book. It w and its history for a long time (two of them for over 40 years!). Now our community has a useful and valuable book that can be used by students and researchers to learn about MCDM and its history. I particularly like the photos which bring the history and its people to life.

Pekka Korhonen Professor of Statistics Aalto University, School of Economics

"This book brings to life — contributors, contributions, activities — the evolution, growth, and future directions of MCDM, a multidiscipline that embraces all facets of decision maki Kudos to three highly distinguished MCDM scholars who have written a classic, which sho be essential reading and serve as a resource for scholars in all academic and professio disciplines."

Herb Moskowitz Purdue University Retired Professor

Multiple Criteria Decision Making (MCDM) is all about making choices in the presence of multiple conflicting criteria. MCDM has become one of the most important and fastest growing subfields of Operations Research/Management Science. As modern MCDM started to emerge about 50 years ago, it is now a good time to take stock of developments. This book aims to present an informal, nontechnical history of MCDM, supplemented with many pictures. It covers the major developments in MCDM, from early history until now. It also covers fascinating discoveries by Nobel Laureates and other prominent scholars. The book begins with the early history of MCDM, which covers the roots of MCDM through the 1960s. It proceeds to give a decade-by-decade account of major developments in the field starting from the 1970s until now. Written in a simple and accessible manner, this book will be of interest to students, academics, and professionals in the field of decision sciences.

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