A New Design of Genetic Algorithm for Solving TSP

Yingying Yu, Yan Chen, Taoying Li
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引用次数: 33

Abstract

In this paper, we develop an algorithm that is able to quickly obtain an optimal solution to TSP from a huge search space. This algorithm is based upon the use of Genetic Algorithm techniques. The algorithm employs a roulette wheel based selection mechanism, the use of a survival-of-the-fittest strategy, a heuristic crossover operator, and an inversion operator. To illustrate it more clearly, a program based on this algorithm has been implemented, which presents the changing process of the route iteration in a more intuitive way. Finally, we apply it into a TSP problem with fifty cities. By comparing with other published techniques, we can easily know that the proposed algorithm can efficiently complete the search process and derive a better solution.
求解TSP的一种新的遗传算法设计
在本文中,我们开发了一种能够从巨大的搜索空间中快速获得TSP最优解的算法。该算法基于遗传算法技术的使用。该算法采用基于轮盘赌的选择机制,使用适者生存策略,启发式交叉算子和反转算子。为了更清楚地说明这一点,基于该算法实现了一个程序,更直观地呈现了路线迭代的变化过程。最后,我们将其应用于50个城市的TSP问题。通过与其他已发表的算法的比较,我们可以很容易地知道,该算法可以有效地完成搜索过程,并得到更好的解。
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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