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首页> 外文期刊>Japanese journal of fuzzy theory and systems >Interactive fuzzy programming for multi-level 0-1 programming problems through genetic algorithms with double strings
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Interactive fuzzy programming for multi-level 0-1 programming problems through genetic algorithms with double strings

机译:通过双弦遗传算法进行多级0-1编程问题的交互式模糊编程

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摘要

This paper presents interactive fuzzy programming for multi-level 0-1 programming problems through genetic algorithms. In fuzzy programming for multi-level linear programming problems, recently developed by Lai et al., since the fuzzy goals are determined for both an objective function and decision variables at the upper level, undesirable solutions are produced when these fuzzy goals are inconsistent. In order to overcome such problems, after eliminating the fuzzy goals for decision variables, interactive fuzzy programming for multi-level 0-1 programming problems through genetic algorithms is presented. In our interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating the satisfactory degrees of decision makers at the upper level with considerations of overall satisfactory balance among all levels. Illustrative numerical examples for two-level and three-level 0-1 programming problems are provided to demonstrate the feasibility of the proposed method.
机译:本文通过遗传算法介绍了多级0-1编程问题的交互式模糊编程。在模糊编程中的多级线性规划问题,最近由Lai等人开发,因为在上层的目标函数和决策变量确定模糊目标,因此当这些模糊目标不一致时产生不良解决方案。为了克服这些问题,在消除了决策变量的模糊目标之后,呈现了通过遗传算法的多级0-1编程问题的交互式模糊编程。在我们的互动方法中,在确定各级决策者的模糊目标之后,通过在各级的总体令人满意的平衡的考虑到较高水平的令人满意的决策者,有效地获得了令人满意的解决方案。提供了两级和三级0-1编程问题的说明性数值示例,以证明所提出的方法的可行性。

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