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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Improved Particle Swarm Optimization Algorithm Based on Periodic Evolution Strategy
verfasst von : Congli Mei, Jing Zhang, Zhiling Liao, Guohai Liu
Erschienen in: Advanced Research on Computer Science and Information Engineering
Verlag: Springer Berlin Heidelberg
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This paper proposed a novel improved PSO algorithm based on an periodic evolution strategy (PSO-PES). From experiments, we observe that the novel search strategy enables the improved PSO to make use of swarm’s information on velocity more effectively to generate better quality solutions iteratively when compared to exiting PSO variants. And PSO-PES significantly improves the PSO’s performance and gives the better performance than original PSO. Another attractive property of the improved PSO is that it does not introduce any complex operations to the original simple PSO framework. The only difference from the standard PSO is the best solution will update by a periodic evolution strategy. PSO-PES is also simple and easy to implement like the original PSO.