Parameters analysis of PSO algorithm in intelligent system optimization

被引：0

作者：

Zhang, Jiashun ^{[1
]}

Lv, Rongjie ^{[2
]}

Wang, Ling ^{[3
]}

机构：

[1] Department of Transportation, School of Civil Engineering, Hebei University of Technology, Tianjin

[2] School of Management, Hebei University of Technology, Tianjin

[3] Department of Civil Engineering, School of Civil Engineering, Hebei University of Technology, Tianjin

来源：

Journal of Applied Sciences | 2013年 / 13卷 / 22期

关键词：

Acceleration constants; Inertia weight; Intelligent system optimization; Parameter analysis; PSO; TSP;

D O I：

10.3923/jas.2013.5498.5502

中图分类号：

学科分类号：

摘要：

With the rapid development of intelligent system, real time optimization become more and more urgent. Particle Swarm Optimization (PSO) is one of the most effective algorithms in solving such problems. Considered the complexity of intelligent system optimization, speed-up technique is needed. As many optimization problems can be converted to travelling salesman problem, the standard benchmark problem of TSP with 31 cities is employed to analyze the relationship between optimal solution and different parameters. The effect on average of the optimal solution, optimal solution, convergence speed and stability of the optimal solution of different parameters are analyzed. Finally, a comparation with ant colony algorithm is conducted and suitable values of parameters are proposed. © 2013 Asian Network for Scientific Information.

引用

页码：5498 / 5502

页数：4

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