Back close

An investigation on mixing heterogeneous differential evolution variants in a distributed framework

Publication Type : Journal Article

Publisher : International Journal of Bio-Inspired Computation, Inderscience Publishers

Source : International Journal of Bio-Inspired Computation, Inderscience Publishers, Volume 7, Number 5, p.307-320 (2015)

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-84945175054&partnerID=40&md5=3afa95d74dbf2b1725ea3027bb4b9004

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2015

Abstract : This paper attempts a preliminary investigation to gain insight about the cooperative dynamics of mixing the four classical differential evolution (DE) variants viz. DE/rand/1/bin, DE/best/1/bin, DE/rand/2/bin and DE/best/2/bin in an island-based distributed framework. The exhaustive combinations of the above said four DE variants in an island size of 4, resulting in 35 distributed DE variants, have all been implemented and tested on 14 unconstrained test functions with diverse features grouped by their modality and decomposability. Simulation results show that the rand-best variants' mixing, display a better cooperative characteristics than rand-rand and best-best variants' mixing. This insight motivated for further investigations on mixing DE/rand-to-best/1/bin (a variant which intrinsically employs rand and best strategies) with DE/rand/1/bin and DE/best/1/bin in the distributed framework. Simulation results reiterated the observations about the cooperative characteristics of rand-best variants' combinations with the latter mixing showing still better cooperative characteristics both in terms of probability of convergence and convergence rate. Copyright © 2015 Inderscience Enterprises Ltd.

Cite this Research Publication : Dr. Thangavelu S. and Dr. Shunmuga Velayutham C., “An investigation on mixing heterogeneous differential evolution variants in a distributed framework”, International Journal of Bio-Inspired Computation, vol. 7, pp. 307-320, 2015.

Admissions Apply Now