Improved differential evolution via cuckoo search operator

Authors:
Pakarat Musigawan;Sirapat Chiewchanwattana;Khamron Sunat
Affiliations:
Department of Computer Science, Khon Kaen University, Khon Kaen, Thailand;Department of Computer Science, Khon Kaen University, Khon Kaen, Thailand;Department of Computer Science, Khon Kaen University, Khon Kaen, Thailand
Venue:
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
Year:
2012

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Abstract

Differential Evolution (DE) is a very popular optimization algorithm for solving numerical optimization problems. It is simple yet powerful algorithm, which has shown effective performance in many optimization problems. In this paper, DECSO that uses the Abandon operator of Cuckoo search to improve the exploration ability of the original DE was proposed. The experimental studies on ten well-known benchmark functions have shown that the proposed approach has efficient search power and fast convergence.