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Empirical study on migration topologies and migration policies for island based distributed differential evolution variants

Publication Type : Conference Proceedings

Publisher : Lecture Notes in Computer Science

Source : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 6466 LNCS, Chennai, p.29-37 (2010)

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-78650878720&partnerID=40&md5=234ccad927211db3f6e1bef884ff7479

ISBN : 3642175627; 9783642175626

Keywords : Differential Evolution, Empirical performance analysis, Empirical studies, Evolutionary algorithms, Global optimization, Global optimization problems, Island Based Distributed Differential Evolution, Migration policy, Migration topology, Optimization, Ring topology, Topology, Unconstrained Global Optimization

Campus : Coimbatore

School : School of Engineering

Center : Center for Computational Engineering and Networking

Department : Computer Science

Verified : Yes

Year : 2010

Abstract : In this paper we present an empirical performance analysis of fourteen variants of Differential Evolution (DE) on a set of unconstrained global optimization problems. The island based distributed differential evolution counterparts of the above said 14 variants have been implemented with mesh and ring migration topologies and their superior performance over the serial implementation has been demonstrated. The competitive performance of ring topology based distributed differential evolution variants on the chosen problem has also been demonstrated. Six different migration policies are experimented for ring topology, and their performances are reported. © 2010 Springer-Verlag.

Cite this Research Publication : Dr. Jeyakumar G. and Dr. Shunmuga Velayutham C., “Empirical study on migration topologies and migration policies for island based distributed differential evolution variants”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6466 LNCS, pp. 29-37, 2010.

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