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

Authors: S. Thangavelu; C. Shunmuga Velayutham

Addresses: Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, India ' Department of Computer Science and Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, India

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.

Keywords: distributed differential evolution; dDE; heterogeneous differential evolution; cooperative dynamics; differential evolution variants; simulation; convergence probability; convergence rate.

DOI: 10.1504/IJBIC.2015.072259

International Journal of Bio-Inspired Computation, 2015 Vol.7 No.5, pp.307 - 320

Received: 06 Nov 2013
Accepted: 18 Nov 2014
Published online: 07 Oct 2015 *

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