An interactive fuzzy satisficing method based on second-order stochastic dominance for multiobjective stochastic programming problems

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  • 多目的確率計画問題に対する二次確率優越に基づく対話型ファジィ満足化手法
  • タモクテキ カクリツ ケイカク モンダイ ニ タイスル ニジ カクリツ ユウエツ ニ モトズク タイワガタ ファジィ マンゾクカ シュホウ

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Abstract

There have been proposed several methods to derive a satisficing solution of the decision maker for multiobjective stochastic programming problems based on the expectation optimization model and the variance minimization model. Satisficing solutions based on these models, however, do not always satisfy the expected utility maximization principle such that the decision maker aims to maximize the expectation of the utility function to express the satisfaction degree of the decision maker for objective functions in uncertain decision making situations. In the meanwhile, there exists a concept to make an ordering of random variables using the second-order distribution function which is the integral of the distibution function, called the second-order stocastic dominance. When the utility function of the decision maker is risk-averse, the second-order stocastic dominance is consistent with the expected utility maximization principle. Therefore, in this paper, we focus on multiobjective stochastic programming problems. After the definition of Pareto optimality based on the second-order stocastic dominance, we propose an interactive fuzzy satisficing method to derive satisficing solutions which are consistent with the expected utility maximization principle for multiobjective stochastic programming problems.

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