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

机译:基于遗传算法的概率最大化模型的交互式模糊规划,用于涉及随机变量系数的两级整数规划问题

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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.
机译:在本文中,我们关注目标函数和/或约束中具有随机变量系数的两级整数规划问题。在随机规划中使用机会约束规划方法,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。在为目标函数引入模糊目标之后,我们考虑使用交互式模糊规划技术来为决策者得出满意的解决方案。由于交互式模糊规划技术必须解决几个整数规划问题,因此我们将针对整数规划问题设计的遗传算法纳入其中。提供了一个说明性的数值示例,以证明所提出方法的可行性。

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