An interactive fuzzy satisficing method for multiobjective 0-1 programming problems with fuzzy numbers through genetic algorithms with double strings

作     者：Sakawa, M Shibano, T 

作者机构：Hiroshima Univ Fac Engn Dept Ind & Syst Engn Higashihiroshima 739 Japan Sinryou Cooperat Syst Prod Div Yokohama Kanagawa 22081 Japan 

出 版 物：《EUROPEAN JOURNAL OF OPERATIONAL RESEARCH》 (Eur J Oper Res)

年 卷 期：1998年第107卷第3期

页      面：564-574页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 

主　　题：multiobjective 0-1 programming fuzzy numbers fuzzy goals alpha-Pareto optimal interactive methods genetic algorithms 

摘      要：In this paper, by considering the experts vague or fuzzy understanding of the nature of the parameters in the problem-formulation process, multiobjective 0-1 programming problems involving fuzzy numbers are formulated. Using the alpha-level sets of fuzzy numbers, the corresponding nonfuzzy alpha-programming problem is introduced. The fuzzy goals of the decision maker (DM) for the objective functions are quantified by eliciting the corresponding linear membership functions. Through the introduction of an extended Pareto optimality concept, if the DM specifies the degree a and the reference membership values, the corresponding extended Pareto optimal solution can be obtained by solving the augmented minimax problems through genetic algorithms with double strings. Then an interactive fuzzy satisficing method for deriving a satisficing solution for the DM efficiently from an extended Pareto optimal solution set is presented. An illustrative numerical example is provided to demonstrate the feasibility and efficiency of the proposed method. (C) 1998 Elsevier Science B.V. All rights reserved.