Interactive fuzzy programming based on a probability maximization model using genetic algorithms for two-level integer programming problems involving random variable coefficients

Kosuke Kato, M. Sakawa
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Abstract

In this paper, we focus on two-level integer programming problems with random variable coefficients in objective functions and/or constraints. Using chance constrained programming approaches in stochastic programming, the stochastic two-level integer programming problems are transformed into deterministic two-level integer programming problems. After introducing fuzzy goals for objective functions, we consider the application of the interactive fuzzy programming technique to derive a satisfactory solution for decision makers. Since several integer programming problems have to be solved in the interactive fuzzy programming technique, we incorporate a genetic algorithm designed for integer programming problems into it. An illustrative numerical example is provided to demonstrate the feasibility of the proposed method.
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基于遗传算法的概率最大化模型的交互式模糊规划求解随机变系数两级整数规划问题
本文主要研究目标函数和/或约束条件下具有随机变系数的两级整数规划问题。利用随机规划中的机会约束规划方法,将随机两级整数规划问题转化为确定性两级整数规划问题。在引入目标函数的模糊目标后,我们考虑了交互式模糊规划技术的应用,以得到决策者满意的解。由于交互式模糊规划技术中需要解决若干整数规划问题,我们将一种针对整数规划问题设计的遗传算法引入其中。算例说明了该方法的可行性。
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