Particle Swarms for Multimodal Optimization

Authors:
Ender Özcan;Murat Yılmaz
Affiliations:
Yeditepe University, Department of Computer Engineering, 34755 Kadıköy/İstanbul, Turkey;Yeditepe University, Department of Computer Engineering, 34755 Kadıköy/İstanbul, Turkey
Venue:
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Year:
2007

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Abstract

In this paper, five previous Particle Swarm Optimization (PSO) algorithms for multimodal function optimization are reviewed. A new and a successful PSO based algorithm, named as CPSO is proposed. CPSO enhances the exploration and exploitation capabilities of PSO by performing search using a random walk and a hill climbing components. Furthermore, one of the previous PSO approaches is improved incredibly by means of a minor adjustment. All algorithms are compared over a set of well-known benchmark functions.