Hybrid ant colony algorithm based on scale compression

被引：0
|
作者：
Yan, Jian-Feng [1 ]
Li, Wei-Hua [1 ]
Du, Bei [1 ]
机构：
[1] School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China
来源：
Kongzhi yu Juece/Control and Decision | 2007年 / 22卷 / 09期
关键词：
Ant colony algorithm - Regional character - Scale compression - Segment;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
To improve the performance of ant colony algorithm in solving large-scale TSP problem, a hybrid ant colony algorithm based on scale compression is proposed. Genetic algorithm is used to generate a suboptimal solution set and calculate their intersection. By eliminating all cities mapped by the elements among the intersection in the primal TSP problem, the original problem is converted into a new one with smaller scale. In addition, an optimal state transition rule is designed based on regional characteristics of optimal solutions to accelerate convergence speed. Simulation results show the approach possesses high searching ability and excellent convergence performance.
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页码：1061 / 1064
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