A two person zero sum matrix game with fuzzy goals and fuzzy payoffs is considered and its solution is conceptualized using a suitable defuzzification function. Also, it is proved that such a game is equivalent to a p...
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A two person zero sum matrix game with fuzzy goals and fuzzy payoffs is considered and its solution is conceptualized using a suitable defuzzification function. Also, it is proved that such a game is equivalent to a primal-dual pair of certain fuzzy linear programming problems in which both goals as well as parameters are fuzzy. (c) 2004 Elsevier Ltd. All rights reserved.
In this paper, a kind of ranking system, called agent-clients evaluation system, is proposed and investigated where there is no such an authority with the right to predetermine weights of attributes of the entities ev...
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In this paper, a kind of ranking system, called agent-clients evaluation system, is proposed and investigated where there is no such an authority with the right to predetermine weights of attributes of the entities evaluated by multiple evaluators for obtaining an aggregated evaluation result from the given fuzzy multi-attribute values of these entities. Three models are proposed to evaluate the entities in such a system based on fuzzy inequality relation, possibility, and necessity measures, respectively. In these models, firstly the weights of attributes are automatically sought by fuzzylinearprogramming (FLP) problems based on the concept of data envelopment analysis (DEA) to make a summing-up assessment from each evaluator. Secondly, the weights for representing each evaluator's credibility are obtained by FLP to make an integrated evaluation of entities from the viewpoints of all evaluators. Lastly, a partially ordered set on a one-dimensional space is obtained so that all entities can be ranked easily. Because the weights of attributes and evaluators are obtained by DEA-based FLP problems, the proposed ranking models can be regarded as fair-competition and self-organizing ones so that the inherent feature of evaluation data can be reflected objectively.
We propose a two-phase approach to solve the fuzzy linear programming problem. Although several methods in the literature have been proposed to treat this problem, the two-phase approach has the merit stated as: if th...
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We propose a two-phase approach to solve the fuzzy linear programming problem. Although several methods in the literature have been proposed to treat this problem, the two-phase approach has the merit stated as: if the decision maker is seeking an efficient solution which can improve the max-min operators' solution so that each membership degree should be improved, then the two-phase method automatically attains this desire if there is room to improve. An interpretation of this result is that the two-phase method not just pursue the highest membership degree in the objective, but also pursue a better utilization of each constrained resource. (C) 1999 Elsevier Science B.V. All rights reserved.
For a fuzzy multi-objective linearprogrammingproblem, we propose a substitute problem. The problem is given as the minimization problem, the objective function of which is the distance between the l-ary restricted a...
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For a fuzzy multi-objective linearprogrammingproblem, we propose a substitute problem. The problem is given as the minimization problem, the objective function of which is the distance between the l-ary restricted alpha-optimal values at each alpha-optimal solutions (Kuwano et al., 1994) and l-ary objective functions with fuzzy parameters.
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