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Solving multi-objective transportation problems by spanning tree-based genetic algorithm

机译:通过跨越树的遗传算法解决多目标运输问题

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In this paper, we present a new approach which is spanning tree-based genetic algorithm for solving a multi-objective transportation problem. The transportation problem as a special type of the network optimization problems has the special datastructure in solution characterized as a transportation graph. In encoding transportation problem, we introduce one of node encodings based on a spanning tree which is adopted as it is capable of equally and uniquely representing all possible basicsolutions. The crossover and mutation were designed based on this encoding. Also we designed the criterion that chromosome has always feasibility converted to a transportation tree. In the evolutionary process, the mixed strategy with (μ+A)-selection and roulette wheel selection is used. Numerical experiments show the effectiveness and efficiency of the proposed algorithm.
机译:在本文中,我们提出了一种新的方法,它是基于树的基于树的遗传算法,用于解决多目标运输问题。作为一种特殊类型的网络优化问题的运输问题在解决方案中具有特殊的数据结构,其特征在于作为运输图。在编码运输问题时,我们基于生成树介绍一个节点编码,其被采用,因为它能够同样地且唯一地代表所有可能的基础机构。基于该编码设计了交叉和突变。此外,我们设计了染色体始终可行性转换为运输树的标准。在进化过程中,使用具有(μ+ a)的混合策略 - 选择和轮盘轮选择。数值实验表明了所提出的算法的有效性和效率。

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