Aspiration Based Decision Analysis and Support Part I: Theoretical and Methodological Backgrounds

In the interdisciplinary and intercultural systems analysis that constitutes the main theme of research in IIASA, a basic question is how to analyze and support decisions with help of mathematical models and logical procedures. This question -- particularly in its multi-criteria and multi-cultural dimensions -- has been investigated in System and Decision Sciences Program (SDS) since the beginning of IIASA. Researchers working both at IIASA and in a large international network of cooperating institutions contributed to a deeper understanding of this question. Around 1980, the concept of reference point multiobjective optimization was developed in SDS. This concept determined an international trend of research pursued in many countries cooperating with IIASA as well as in many research programs at IIASA -- such as energy, agricultural, environmental research. SDS organized since this time numerous international workshops, summer schools, seminar days and cooperative research agreements in the field of decision analysis and support. By this international and interdisciplinary cooperation, the concept of reference point multiobjective optimization has matured and was generalized into a framework of aspiration based decision analysis and support that can be understood as a synthesis of several known, antithetical approaches to this subject -- such as utility maximization approach, or satisficing approach, or goal -- program -- oriented planning approach. Jointly, the name of quasisatisficing approach can be also used, since the concept of aspirations comes from the satisficing approach. Both authors of the Working Paper contributed actively to this research: Andrzej Wierzbicki originated the concept of reference point multiobjective optimization and quasisatisficing approach, while Andrzej Lewandowski, working from the beginning in the numerous applications and extensions of this concept, has had the main contribution to its generalization into the framework of aspiration based decision analysis and support systems. This paper constitutes a draft of the first part of a book being prepared by these two authors. Part I, devoted to theoretical foundations and methodological background, written mostly by Andrzej Wierzbicki, will be followed by Part II, devoted to computer implementations and applications of decision support systems based on mathematical programming models, written mostly by Andrzej Lewandowski. Part III, devoted to decision support systems for the case of subjective evaluations of discrete decision alternatives, will be written by both authors.

[1]  A. Charnes,et al.  Goal programming and multiple objective optimizations: Part 1 , 1977 .

[2]  Kenneth O. Kortanek,et al.  A biextremal principle for a behavioral theory of the firm , 1982 .

[3]  Hirotaka Nakayama,et al.  Theory of Multiobjective Optimization , 1985 .

[4]  E. Kalai,et al.  OTHER SOLUTIONS TO NASH'S BARGAINING PROBLEM , 1975 .

[5]  W. Hamilton,et al.  The Evolution of Cooperation , 1984 .

[6]  John Kenneth Galbraith,et al.  The New Industrial State , 1968 .

[7]  V. Bowman.  On the Relationship of the Tchebycheff Norm and the Efficient Frontier of Multiple-Criteria Objectives , 1976 .

[8]  G. Debreu,et al.  Theory of Value , 1959 .

[9]  J. Neumann,et al.  Theory of games and economic behavior , 1945, 100 Years of Math Milestones.

[10]  Abu S.M. Masud,et al.  Interactive Sequential Goal Programming , 1981 .

[11]  Manfred Grauer,et al.  The Reference Point Optimization Approach - Methods of Efficient Implementation , 1982 .

[12]  S. Zionts,et al.  An Interactive Programming Method for Solving the Multiple Criteria Problem , 1976 .

[13]  G. Leitmann,et al.  Compromise Solutions, Domination Structures, and Salukvadze’s Solution , 1974 .

[14]  Johannes Jahn,et al.  Scalarization in vector optimization , 1984, Math. Program..

[15]  A. Wierzbicki.  Multiobjective Trajectory Optimization and Model Semiregularization , 1981 .

[16]  Hirotaka Nakayama.  On the Components in Interactive Multiobjective Programming Methods , 1985 .

[17]  Andrzej P. Wierzbick.  Basic properties of scalarizmg functionals for multiobjective optimization , 1977 .

[18]  M. V. Mikhalevich.  Stochastic Approaches to Interactive Multi-Criteria Optimization Problems , 1986 .

[19]  Stuart A. Umpleby.  A Group Process Approach to Organizational Change , 1982, International Working Conference on Model Realism.

[20]  Derek W. Bunn,et al.  MCDM: Past Decade and Future Trends , 1986 .

[21]  W. Orchard-Hays,et al.  An Implementation of the Reference Point Approach for Multiobjective Optimization , 1980 .

[22]  Johannes Jahn,et al.  Some characterizations of the optimal solutions of a vector optimization problem , 1985 .

[23]  Peter C. Fishburn,et al.  Utility theory for decision making , 1970 .

[24]  Pekka Korhonen,et al.  A Visual Interactive Method for Solving the Multiple-Criteria Problem , 1986 .

[25]  Andrzej P. Wierzbicki,et al.  A Methodological Guide to Multiobjective Optimization , 1980 .

[26]  R. Tietz,et al.  On the Structure, Stabilization and Accuracy of the Decision Process , 1985 .

[27]  H. Simon,et al.  Models of Man. , 1957 .

[28]  Laszlo Zsolnai,et al.  DIFFERENT DISSOLUTIONS OF THE MAN-AND-WORLD PROBLEM , 1985 .

[29]  M. I. Henig.  Proper efficiency with respect to cones , 1982 .

[30]  J. Dyer.  Interactive Goal Programming , 1972 .

[31]  H. P. Benson,et al.  Existence of efficient solutions for vector maximization problems , 1978 .

[32]  H. Raiffa,et al.  The art and science of negotiation , 1983 .

[33]  Yuri Ermoliev,et al.  Simultaneous Nonstationary Optimization, Estimation and Approximation Procedures , 1982 .

[34]  John Casti,et al.  Vector-valued optimization problems in control theory , 1979 .

[35]  R. L. Keeney,et al.  Decisions with Multiple Objectives: Preferences and Value Trade-Offs , 1977, IEEE Transactions on Systems, Man, and Cybernetics.

[36]  Joseph G. Ecker,et al.  Finding efficient points for linear multiple objective programs , 1975, Math. Program..

[37]  G. Fandel.  Optimale Entscheidung bei mehrfacher Zielsetzung , 1972 .

[38]  T. Gal.  On Efficient Sets in Vector Maximum Problems — A Brief Survey , 1986 .

[39]  János Kornai,et al.  Anti-Equilibrium: On Economic Systems Theory and the Tasks of Research , 1971 .

[40]  R. E. Kalman,et al.  New Results in Linear Filtering and Prediction Theory , 1961 .

[41]  Masatoshi Sakawa,et al.  Interactive fuzzy decisionmaking for multiobjective nonlinear programming problems , 1984 .

[42]  A. Wierzbicki.  A Mathematical Basis for Satisficing Decision Making , 1982 .

[43]  W. B. Gearhart.  Characterization of properly efficient solutions by generalized scalarization methods , 1983 .

[44]  Anatol Rapoport,et al.  USES OF EXPERIMENTAL GAMES , 1985 .

[45]  Heinz Roland Weistroffer.  A combined over- and under-achievement programming approach to multiple objectives decision-making , 1984 .

[46]  Howard Raiffa,et al.  Games And Decisions , 1958 .

[47]  J. Nash.  THE BARGAINING PROBLEM , 1950, Classics in Game Theory.

[48]  Andrzej P. Wierzbicki,et al.  Negotiation and Mediation in Conflicts I.: The Role of Mathematical Approaches and Methods , 1983 .

[49]  M. Mesarovic,et al.  Theory of Hierarchical, Multilevel, Systems , 1970 .

[50]  Andrzej P. Wierzbicki.  Penalty Methods in Solving Optimization Problems with Vector Performance Criteria, II , 1975 .

[51]  Yacov Y. Haimes,et al.  Multiobjective optimization in water resources systems : the surrogate worth trade-off method , 1975 .

[52]  H. Górecki,et al.  Decision Support Based on the Skeleton Method — The HG Package , 1985 .

[53]  A. Ingham,et al.  Aspiration Levels in Bargaining and Economic Decision Making , 1984 .