Fuzzy option prioritization for the graph model for conflict resolution

Abstract A fuzzy option prioritization technique is developed to efficiently model uncertain preferences of DMs in strategic conflicts as fuzzy preferences by using the decision makers' (DMs') fuzzy truth values of preference statements at feasible states within the framework of the Graph Model for Conflict Resolution. The preference statements of a DM express desirable combinations of options or courses of action, and are listed in order of importance. A fuzzy truth value is a truth degree, expressed as a number between 0 and 1, capturing uncertainty in the truth of a preference statement at a feasible state. A fuzzy preference formula is introduced based on the fuzzy truth values of preference statements, and it is established that the output of this formula is a fuzzy preference relation. It is shown that fuzzy option prioritization can also be used when the truth values of preference statements at feasible states are completely based on Boolean logic, thereby generating a crisp preference over feasible states that is the same as would be found by employing the existing crisp option prioritization, making the crisp option prioritization technique a special case of the fuzzy option prioritization methodology. To demonstrate how this methodology can be employed to represent fuzzy preferences in real-world decision problems, fuzzy option prioritization is applied to an actual dispute over groundwater contamination that took place in Elmira, Ontario, Canada.

[1]  Keith W. Hipel,et al.  Fuzzy truth values in option prioritization for preference elicitation in the Graph Model , 2012, 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[2]  Z. S. Xu,et al.  The uncertain OWA operator , 2002, Int. J. Intell. Syst..

[3]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[4]  Keith W. Hipel,et al.  Representing ordinal preferences in the decision support system GMCR II , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[5]  Keith W. Hipel,et al.  The decision support system GMCR II in negotiations over groundwater contamination , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[6]  T. Ross Fuzzy Logic with Engineering Applications , 1994 .

[7]  Wilfrid Hodges,et al.  Mathematical logic , 2007, Oxford texts in logic.

[8]  Keith W. Hipel,et al.  Fuzzy preferences in multiple participant decision making , 2011, Sci. Iran..

[9]  Keith W. Hipel,et al.  Fuzzy preferences in the sustainable development conflict , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.

[10]  K. Nakamura Preference relations on a set of fuzzy utilities as a basis for decision making , 1986 .

[11]  Michael Bartholomew-Biggs,et al.  Nonlinear Optimization with Engineering Applications , 2008 .

[12]  S. Orlovsky Decision-making with a fuzzy preference relation , 1978 .

[13]  Charles Leake Interactive Decision Making: The Graph Model for Conflict Resolution , 1993 .

[14]  John Peng A decision support system for conflict resolution , 1999 .

[15]  Bernadette Bouchon-Meunier,et al.  Modern Information Processing: From Theory to Applications , 2011 .

[16]  Keith W. Hipel,et al.  Coalition Analysis in Group Decision Support , 2001 .

[17]  Keith W. Hipel,et al.  Strategic decision support for the services industry , 2001, IEEE Trans. Engineering Management.

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

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

[20]  Lotfi A. Zadeh,et al.  Fuzzy Logic for Business, Finance, and Management , 1997, Advances in Fuzzy Systems - Applications and Theory.

[21]  Philippe De Wilde Fuzzy utility and equilibria , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[22]  D. Lutz,et al.  Paradoxes of Rationality: Theory of Metagames and Political Behavior , 1973 .

[23]  Francisco Herrera,et al.  Integrating multiplicative preference relations in a multipurpose decision-making model based on fuzzy preference relations , 2001, Fuzzy Sets Syst..

[24]  K. I. M. McKinnon,et al.  Solving Stochastic Ship Fleet Routing Problems with Inventory Management Using Branch and Price , 2016, Advances in Stochastic and Deterministic Global Optimization.

[25]  Niall M. Fraser Ordinal preference representations , 1994 .

[26]  T. Tanino Fuzzy preference orderings in group decision making , 1984 .

[27]  Zeshui Xu,et al.  A survey of preference relations , 2007, Int. J. Gen. Syst..

[28]  Tetsuzo Tanino,et al.  Fuzzy Preference Relations in Group Decision Making , 1988 .

[29]  Keith W. Hipel,et al.  A decision support system for interactive decision making-Part I: model formulation , 2003, IEEE Trans. Syst. Man Cybern. Part C.

[30]  Nigel Howard,et al.  Confrontation Analysis: How to Win Operations Other Than War , 1999 .

[31]  D. Marc Kilgour Book review:Theory of moves , 1995 .

[32]  Matthias Ehrgott,et al.  Multiple criteria decision analysis: state of the art surveys , 2005 .

[33]  Niall M. Fraser Applications of preference trees , 1993, Proceedings of IEEE Systems Man and Cybernetics Conference - SMC.

[34]  Keith W. Hipel,et al.  Environmental conflict resolution using the graph model , 1993, Proceedings of IEEE Systems Man and Cybernetics Conference - SMC.

[35]  Keith W. Hipel,et al.  The graph model for conflicts , 1987, Autom..

[36]  Keith W. Hipel,et al.  Fuzzy Preferences in the Graph Model for Conflict Resolution , 2012, IEEE Transactions on Fuzzy Systems.

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

[38]  Luis G. Vargas Conflict analysis: Models and resolutions: Niall M. FRASER and Keith W. HIPEL Volume 11 in: North-Holland Series in System Science and Engineering, North-Holland, New York, 1984, xx + 377 pages, $34.50 , 1985 .

[39]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[40]  Keith W. Hipel,et al.  Fuzzy preferences in a two-decision maker graph model , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.