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New models for shortest path problem with fuzzy arc lengths

机译:具有模糊弧长的最短路径问题的新模型

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摘要

This paper considers the shortest path problem with fuzzy arc lengths. According to different decision criteria, the concepts of expected shortest path, α-shortest path and the most shortest path in fuzzy environment are originally proposed, and three types of models are formulated. In order to solve these models, a hybrid intelligent algorithm integrating simulation and genetic algorithm is provided and some numerous examples are given to illustrate its effectiveness.
机译:本文考虑了弧长模糊的最短路径问题。根据不同的决策标准,提出了模糊环境中期望最短路径,α-最短路径和最短路径的概念,并建立了三种模型。为了解决这些模型,提供了一种融合了模拟和遗传算法的混合智能算法,并给出了许多例子来说明其有效性。

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