4.2 Article

Particle swarm optimization-based algorithms for TSP and generalized TSP

期刊

INFORMATION PROCESSING LETTERS
卷 103, 期 5, 页码 169-176

出版社

ELSEVIER
DOI: 10.1016/j.ipl.2007.03.010

关键词

algorithms; particle swarm optimization; traveling salesman problem; generalized traveling salesman problem; swap operator

向作者/读者索取更多资源

A novel particle swarm optimization (PSO)-based algorithm for the traveling salesman problem (TSP) is presented. An uncertain searching strategy and a crossover eliminated technique are used to accelerate the convergence speed. Compared with the existing algorithms for solving TSP using swarm intelligence, it has been shown that the size of the solved problems could be increased by using the proposed algorithm. Another PSO-based algorithm is proposed and applied to solve the generalized traveling salesman problem by employing the generalized chromosome. Two local search techniques are used to speed up the convergence. Numerical results show the effectiveness of the proposed algorithms. (c) 2007 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.2
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据