Hybrid Particle Swarm Optimization Algorithm for Large-scale Travelling Salesman Problem

被引：0
|
作者：
Zhang, Jiangwei [1 ]
机构：
[1] Xuchang Univ, Int Sch Educ, Xuchang 461000, Henan, Peoples R China
来源：
APPLIED SCIENCE, MATERIALS SCIENCE AND INFORMATION TECHNOLOGIES IN INDUSTRY | 2014年 / 513-517卷
关键词：
Particle Swarm Optimization (PSO); Improved Enhanced Self-Tentative(IEST); Travelling Salesman Problem (TSP); 2-opt Algorithm;
D O I：
10.4028/www.scientific.net/AMM.513-517.1773
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
Based on the improved enhanced self-tentative (IEST) particle swarm optimization (PSO) algorithm, 2-opt local searching algorithm is introduced in the later evolution stage. 2-opt method further strengthen the self-tentative and make up the deficiency of the IEST PSO algorithm and solve the cross solution problem. The hybrid PSO algorithm greatly increases the chances to find the better solution in the evolutionary process. Time complexity of the 2-opt method is analyzed. Based on this the proper parameters is set to solve different benchmark TSP problems, numerical simulation results show the effectiveness and efficiency of the hybrid PSO algorithm.
引用
收藏
页码：1773 / 1778
页数：6
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