遗传算法求解旅行商问题

ACM-SE 28 Pub Date : 1990-04-01 DOI:10.1145/98949.99033
D'Ann Fuquay, L. D. Whitley
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引用次数: 2

摘要

本文描述了一种用于生成旅行推销员问题(TSP)解的遗传方法,并报告了使用科罗拉多大学开发的遗传算法实现(称为GENTfOR)的早期测试结果。该实现使用了一种新的、专门的基因重组算子,该算子具有高度的不确定性,并且不需要知道城市之间的距离就可以进行重组。报告的结果证实了遗传方法的可行性,不仅可以找到TSP的良好解决方案,还可以找到不包含加权边概念的更一般类型的优化问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Genetic algorithm solutions for the traveling salesman problem
A genetic approach (o generating solutions for the traveling salesman problem (TSP) is described and early results of tests are reported using a genetic algo­ rithm implementation known as GENTfOR which was developed at Colorado Stale University. The imple­ mentation uses a new, specialized genetic recombina­ tion operator which incorporates a high degree of nondeterminism and docs not require knowledge of dis­ tance between cities for recombination. Results reported substantiate the viability of the genetic approach for finding good solutions not only to the TSP but also to a more general class of optimization problems that do not incorporate the notion of weighted edges.
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