Design and Application of m-Mutation Operator in Genetic Algorithm to Solve Traveling Salesman Problem

D. N. Mudaliar, N. Modi
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引用次数: 1

Abstract

This research work intends to elucidate Traveling Salesman Problem, a variant of Symmetric Hamiltonian Cycle Problems more capably. A different mutation operator called m-mutation operator for genetic algorithm is proposed to solve this problem. The efficiency of proposed mutation operator is compared with existing mutation operators by retaining the same selection, crossover and fitness function. The mutation operator is tested with data from TSPLIB dataset. The intercity distance table of cities was input to the coded C program which implemented the proposed mutation operator. The same dataset was used to compare the performance of proposed mutation operator with other existing mutation operators. The results of the experiment confirm that proposed mutation operator searches better solutions quicker compared to other mutation operators.
遗传算法中m-变异算子的设计与应用
本文的研究工作旨在对对称哈密顿循环问题的一个变体——旅行商问题进行更详尽的阐述。为了解决这一问题,提出了一种不同的变异算子m-变异算子。通过保留相同的选择、交叉和适应度函数,比较了所提突变算子与现有突变算子的效率。使用TSPLIB数据集的数据对突变算子进行了测试。将城市间距离表输入到编码的C程序中,该程序实现了所提出的变异算子。使用相同的数据集比较了所提出的变异算子与其他现有变异算子的性能。实验结果表明,与其他变异算子相比,所提出的变异算子能更快地搜索到更好的解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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