Re-diversification based particle swarm algorithm with cauchy mutation

Authors:
Hui Wang;Sanyou Zeng;Yong Liu;Wenjun Wang;Hui Shi;Gang Liu
Affiliations:
School of Computer, China University of Geosciences, Wuhan, China and Research Center of Science and Technology, China University of Geosciences, Wuhan, China;School of Computer, China University of Geosciences, Wuhan, China and Research Center of Science and Technology, China University of Geosciences, Wuhan, China;University of Aizu, Aizu-Wakamatsu, Fukushima, Japan;Applied Psychology Institution, China University of Geosciences, Wuhan, China;School of Computer, China University of Geosciences, Wuhan, China and Research Center of Science and Technology, China University of Geosciences, Wuhan, China;School of Computer, China University of Geosciences, Wuhan, China and Research Center of Science and Technology, China University of Geosciences, Wuhan, China
Venue:
ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
Year:
2007

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Abstract

Particle Swarm Optimization (PSO) has shown its fast search speed in many complicated optimization and search problems. However, PSO could often easily fall into local optima. This paper presents a hybrid PSO algorithm called RPSO by applying a new re-diversification mechanism and a dynamic Cauchy mutation operator to accelerate the convergence of PSO and avoid premature convergence. Experimental results on many well-known benchmark optimization problems have shown that the RPSO could successfully deal with those difficult multimodal functions while maintaining fast search speed on those simple unimodal functions in the function optimization.