Jiashun Zhang
Department of Transportation, School of Civil Engineering, Hebei University of Technology, Tianjin, China
Rongjie Lv
School of Management, Hebei University of Technology,Tianjin, China
Ling Wang
Department of Civil Engineering, School of Civil Engineering, Hebei University of Technology, Tianjin, China
ABSTRACT
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.
PDF References Citation
Received: August 02, 2013;
Accepted: October 06, 2013;
Published: November 16, 2013
How to cite this article
Jiashun Zhang, Rongjie Lv and Ling Wang, 2013. Parameters Analysis of Pso Algorithm in Intelligent System Optimization. Journal of Applied Sciences, 13: 5498-5502.
DOI: 10.3923/jas.2013.5498.5502
URL: https://scialert.net/abstract/?doi=jas.2013.5498.5502
DOI: 10.3923/jas.2013.5498.5502
URL: https://scialert.net/abstract/?doi=jas.2013.5498.5502
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