Challenging Decision Problems and Decision Models

In this chapter, we discuss the existing decision models and their limitations for solving real-world decision problems with many illustrations from different domains of human activity. Then we introduce briefly the type of decision problems we will analyse and solve in this book, decision-making in changeable spaces (DMCS) problems. Such decision problems involve dynamic parameters with unknown shapes, dimensions, probability distribution, membership function, etc. The approach and models we develop for solving these problems are based on Habitual Domain theory.

[1]  Moussa Larbani,et al.  Sur l'équilibre fort selon Berge , 2001, RAIRO Oper. Res..

[2]  Howard Raiffa,et al.  Games and Decisions: Introduction and Critical Survey. , 1958 .

[3]  H. Kelley.  Attribution theory in social psychology , 1967 .

[4]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .

[5]  George B. Dantzig,et al.  Linear programming and extensions , 1965 .

[6]  D. Kahneman.  Thinking, Fast and Slow , 2011 .

[7]  R. Słowiński,et al.  Stochastic Versus Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty , 1990, Theory and Decision Library.

[8]  E. W. Adams,et al.  Models of Man, Social and Rational: Mathematical Essays on Rational Human Behavior in a Social Setting , 1962 .

[9]  P. L. Yu,et al.  Habitual Domains , 1991, Oper. Res..

[10]  Po Lung Yu,et al.  Dynamic multiple criteria decision making in changeable spaces: from habitual domains to innovation dynamics , 2012, Ann. Oper. Res..

[11]  A. Tversky,et al.  The framing of decisions and the psychology of choice. , 1981, Science.

[12]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[13]  J. Townsend,et al.  Decision field theory: a dynamic-cognitive approach to decision making in an uncertain environment. , 1993, Psychological review.

[14]  T S Critchfield,et al.  Temporal discounting: basic research and the analysis of socially important behavior. , 2001, Journal of applied behavior analysis.

[15]  Vassili N. Kolokoltsov,et al.  The Interval Market Model in Mathematical Finance: Game-Theoretic Methods , 2012 .

[16]  Cleotilde Gonzalez,et al.  The use of microworlds to study dynamic decision making , 2005, Comput. Hum. Behav..

[17]  D. Kahneman,et al.  Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias , 1991 .

[18]  O. Holsti,et al.  Essence of Decision: Explaining the Cuban Missile Crisis , 1972 .

[19]  E. Hobman,et al.  Household energy use: Applying behavioural economics to understand consumer decision-making and behaviour , 2015 .

[20]  A. Tversky,et al.  Rational choice and the framing of decisions , 1990 .

[21]  Antoine Soubeyran,et al.  Generalized inexact proximal algorithms : habit ’ s formation with resistance to change , following worthwhile changes , 2014 .

[22]  William Samuelson,et al.  Status quo bias in decision making , 1988 .

[23]  Nils Brunsson.  My own book review : The Irrational Organization , 2014 .

[24]  Gerd Gigerenzer,et al.  Why Heuristics Work , 2008, Perspectives on psychological science : a journal of the Association for Psychological Science.

[25]  P. Yu.  Multiple-Criteria Decision Making: "Concepts, Techniques, And Extensions" , 2012 .

[26]  J. Neumann,et al.  Theory of Games and Economic Behavior. , 1945 .

[27]  Po-Lung Yu,et al.  Blinds, fuzziness and habitual domain tools in decision making with changeable spaces , 2010 .

[28]  Po-Lung Yu,et al.  Forming Winning Strategies: An Integrated Theory of Habitual Domains , 1990 .

[29]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[30]  Raimo P. Hämäläinen,et al.  On the importance of behavioral operational research: The case of understanding and communicating about dynamic systems , 2013, Eur. J. Oper. Res..

[31]  P. A. Losty,et al.  A Behavioural Theory of the Firm , 1965 .

[32]  Mokhtar S. Bazaraa,et al.  Nonlinear Programming: Theory and Algorithms , 1993 .

[33]  R. S. Laundy,et al.  Multiple Criteria Optimisation: Theory, Computation and Application , 1989 .

[34]  P. Yu,et al.  A foundation for competence set analysis , 1990 .

[35]  Ichiro Nishizaki,et al.  Fuzzy Stochastic Multiobjective Programming , 2013 .

[36]  Moussa Larbani,et al.  Decision Making and Optimization in Changeable Spaces, a New Paradigm , 2012, J. Optim. Theory Appl..

[37]  A. Tversky.  Intransitivity of preferences. , 1969 .

[38]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[39]  Ward Edwards,et al.  Dynamic Decision Theory and Probabilistic Information Processings1 , 1962 .

[40]  J. Steinbruner.  The Cybernetic Theory of Decision: New Dimensions of Political Analysis , 1974 .

[41]  Kurt Sandkuhl.  Information Logistics in Networked Organizations: Selected Concepts and Applications , 2007, ICEIS.

[42]  O. Svenson,et al.  Decision making : cognitive models and explanations , 1997 .

[43]  B. Brehmer.  Dynamic decision making: human control of complex systems. , 1992, Acta psychologica.