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Combining different differential evolution variants in an island based distributed framework–an investigation

Publication Type : Journal Article

Publisher : Advances in Intelligent Systems and Computing

Source : Advances in Intelligent Systems and Computing, Springer , Volume 320, p.593-606 (2015)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921518483&partnerID=40&md5=02f15ebe752f04ba2a49feb322017165

Keywords : Co-operative evolution, Complementary Search Strategies, Differential Evolution, Distributed differential evolution

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2015

Abstract : This paper proposes to combine three different Differential Evolution (DE) variants viz. DE/rand/1/bin, DE/best/1/bin and DE/rand-to-best/1/bin in an island based distributed Differential Evolution (dDE) framework. The resulting novel dDEs with different DE variants in each islands have been tested on 13 highdimensional benchmark problems (of dimensions 500 and 1000) to observe their performance efficacy as well as to investigate the potential of combining such complementary collection of search strategies in a distributed framework. Simulation results show that rand and rand-to-best strategy combination variants display superior performance over rand, best, rand-to-best as well as best, rand-to-best combination variants. The rand and best strategy combinations displayed the poor performance. The simulation studies indicate a definite potential of combining complementary collection of search characteristics in an island based distributed framework to realize highly co-operative, efficient and robust distributed Differential Evolution variants capable of handling a wide variety of optimizations tasks. © Springer International Publishing Switzerland 2015.

Cite this Research Publication : Dr. Thangavelu S. and Dr. Shunmuga Velayutham C., “Combining different differential evolution variants in an island based distributed framework–an investigation”, Advances in Intelligent Systems and Computing, vol. 320, pp. 593-606, 2015.

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