Abstract

Game theory is considered as an efficient framework in dealing with decision making problems for two players in the competitive environment. In general, the evaluation values of payoffs matrix are expressed by crisp values in a game model. However, many uncertainties and vagueness should be considered due to the qualitative criteria and the subjective judgment of decision makers in the decision making process. The aim of this study is to develop an effective methodology for solving the payoffs matrix with linguistic variables by multiple decision makers in a game model. Based on the linguistic variables, the decision makers can easily express their opinions with respect to criteria for each alternative. By using the linear programming method, we can find the optimal solution of a game matrix in accordance with the combination of strategies of each player effectively. In addition, the expected performance value (EPV) index is defined in this paper to compare the competition ability of each player based on the optimal probability of each strategy combination. And then, numerical example will be implemented to illustrate the computation process of the proposed model. The conclusion and future research are discussed at the end of this paper.

Highlights

  • In decision science field, game theory provides an effective way for handing the interactive optimization problems

  • The aim of this study is to develop an effective methodology for solving the payoffs matrix with linguistic variables by multiple decision makers in a game model

  • Game theory started with the publication of “the theory of games and economics behavior” in 1944 by von Neumann and Morgenstern [1]

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Summary

Introduction

Game theory provides an effective way for handing the interactive optimization problems. Campos [7] proposed a two-person zero sum fuzzy matrix game and applied fuzzy linear programming to calculate the mixed strategy probability of each player. Roy and Das [21] handled the multi-criteria bimatrix goal game problem by determining Ggoal security strategies. They applied the real coded genetic algorithm to acquire the bounds of the objectives of the proposed game. In order to overcome the drawbacks of original game model, the main purpose of this study is to develop a new decision making method, linguistic multiperson multi-criteria game (LMPMCG) model, for dealing with the game problems under multiperson and multi-criteria environment. Conclusion and future research are discussed at the end of this paper

Fuzzy Set and Linguistic Variable
Numerical Example
Aggregating the Evaluations of Experts
F H EH VH
Conclusion and Future Research
Full Text
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