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首页> 外文期刊>Advances in Operations Research >An Interactive Fuzzy Satisficing Method for Multiobjective Nonlinear Integer Programming Problems with Block-Angular Structures through Genetic Algorithms with Decomposition Procedures
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An Interactive Fuzzy Satisficing Method for Multiobjective Nonlinear Integer Programming Problems with Block-Angular Structures through Genetic Algorithms with Decomposition Procedures

机译：遗传算法分解程序求解块角结构多目标非线性整数规划问题的交互式模糊满足方法

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摘要

We focus on multiobjective nonlinear integer programming problems with block-angular structures which are often seen as a mathematical model of large-scale discrete systems optimization. By considering the vague nature of the decision maker's judgments, fuzzy goals of the decision maker are introduced, and the problemis interpreted as maximizing an overall degree of satisfaction with the multiple fuzzy goals. For deriving a satisficing solution for the decision maker, we develop an interactive fuzzy satisficing method. Realizing the block-angular structures that can be exploited in solving problems, we also propose genetic algorithms with decompositionprocedures. Illustrative numerical examples are provided to demonstrate the feasibility and efficiency of the proposed method.
机译：我们关注具有块角结构的多目标非线性整数规划问题，这些问题通常被视为大规模离散系统优化的数学模型。通过考虑决策者判断的模糊性，引入了决策者的模糊目标，并将问题解释为使多个模糊目标的总体满意度达到最大。为了为决策者提供满足的解决方案，我们开发了一种交互式模糊满足的方法。为了实现可用于解决问题的块角结构，我们还提出了具有分解过程的遗传算法。提供了说明性的数值示例，以证明所提出方法的可行性和效率。

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