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An evolutionary game based particle swarm optimization algorithm

โœ Scribed by Wei-Bing Liu; Xian-Jia Wang

Publisher
Elsevier Science
Year
2008
Tongue
English
Weight
455 KB
Volume
214
Category
Article
ISSN
0377-0427

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โœฆ Synopsis

Particle swarm optimization (PSO) is an evolutionary algorithm used extensively. This paper presented a new particle swarm optimizer based on evolutionary game (EGPSO). We map particles' finding optimal solution in PSO algorithm to players' pursuing maximum utility by choosing strategies in evolutionary games, using replicator dynamics to model the behavior of particles. And in order to overcome premature convergence a multi-start technique was introduced. Experimental results show that EGPSO can overcome premature convergence and has great performance of convergence property over traditional PSO.

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