计算机与现代化

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基于改进遗传算法的大规模TSP问题求解方案

  

  1. 阜新高等专科学校,辽宁阜新123000
  • 收稿日期:2014-11-06 出版日期:2015-02-28 发布日期:2015-03-06
  • 作者简介:雷玉梅(1980),女,辽宁阜新人,阜新高等专科学校讲师,硕士,研究方向:计算机软件。

A Solution of Largescale TSP Based on Improved Genetic Algorithm

  1. Fuxin Higher Training College, Fuxin 123000, China
  • Received:2014-11-06 Online:2015-02-28 Published:2015-03-06

摘要: TSP问题不仅描述旅行商周游城市的问题,也是许多工程领域中复杂问题的抽象形式,找到一种有效的TSP问题求解方案具有十分重要的意义。针对大规模TSP问题中最小回路代价的求解问题,提出一种基于遗传算法的大规模TSP问题的求解方案,采用分而治之的思想,并对传统遗传算法的初始化和遗传算子进行改进,提高了算法性能。多个数据集上的实验结果证明了提出的算法能够优化收敛结果,一定程度上解决过早收敛的问题。

关键词: 大规模TSP问题, 最短路径, 遗传算法, 改进遗传算法

Abstract: TSP not only describes the problem of travelling around a number of cities, but also stands for a number of problems in some other fields. Thus, it is meaningful to find an effective solution to largescale TSP. As for the solution to find the minimum distance of a loop consisting of a large number of cities in TSP, in this paper, we propose such a new solution based on genetic algorithms. It adopts the idea of dividing and ruling, and utilizes a genetic algorithm based on improved initialization method and genetic operators to improve its performance. Experimental results across multiple datasets illustrate the proposed algorithm performs well in optimizing convergence result and solving the problem of premature convergence to some extent.

Key words: scale TSP; shortest path; genetic algorithm, improved genetic algorithm

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