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Genetic algorithm approach for solving multi-objective fuzzy stochastic programming problem

机译:遗传算法求解多目标模糊随机规划问题

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摘要

This paper is concerned with the solution procedure of a multi-objective fuzzy stochastic optimisation problem by simulation-based genetic algorithm. In this article, a multi-objective fuzzy chance constrained programming problem is considered with continuous fuzzy random variables. The uncertain parameters are considered as fuzzy normal and fuzzy log-normal random variables. The feasibilities of the fuzzy chance constraints are checked by the fuzzy stochastic programming with the genetic process without deriving the deterministic equivalents. The proposed procedure is illustrated by a numerical example.
机译:本文研究了基于仿真的遗传算法求解多目标模糊随机优化问题的过程。本文考虑具有连续模糊随机变量的多目标模糊机会约束规划问题。不确定参数被视为模糊正态和模糊对数正态随机变量。模糊机会约束的可行性通过带有遗传过程的模糊随机规划来检验,而无需得出确定性等价物。数值示例说明了所建议的过程。

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