A new hybrid algorithm of particle swarm optimization

Authors:
Guangyou Yang;Dingfang Chen;Guozhu Zhou
Affiliations:
,School of Mechanical Engineering, Hubei University of Technology, Wuhan, China;Lab of intelligent manufacturing & control, Wuhan University of Technology, Wuhan, China;School of Mechanical Engineering, Hubei University of Technology, Wuhan, China
Venue:
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
Year:
2006

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Abstract

This paper presents a new hybrid algorithm of particle swarm optimization (PSO) called PSOSA, in which the mechanism of modified simulated annealing (SA) is embedded into standard PSO algorithm. The proposed algorithm not only keeps the characters of simple and easy to be implemented, but also enhances the ability of getting rid of local optimum and improves the speed and precision of convergence. The testing results of several benchmark functions with different dimensions show that the proposed algorithm is superior to standard PSO and the other PSO algorithms.