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Analyzing the Explorative power of Differential Evolution Variants on Different Classes of Problems

Publication Type : Conference Proceedings

Publisher : Springer-Verlag

Source : Lecture Notes in Computer Science (LNCS-6466), Springer-Verlag, Volume 6466, p.95-102 (2010)

Url : https://link.springer.com/chapter/10.1007/978-3-642-17563-3_12

Campus : Coimbatore

School : School of Engineering

Center : Amrita Innovation & Research

Department : Computer Science

Verified : Yes

Year : 2010

Abstract : This paper is focusing on comparing the performance of Differential Evolution (DE) variants, in the light of analyzing their Explorative power on a set of benchmark function. We have chosen fourteen different variants of DE and fourteen benchmark functions grouped by feature: Unimodal Separable, Unimodal NonSeparable, Multimodal Separable and Multimodal NonSeparable. Fourteen variants of DE were implemented and tested on these fourteen functions for the dimension of 30. The explorative power of the variants is evaluated and analyzed by measuring the evolution of population variance, at each generation. This analysis provides insight about the competitiveness of DE variants in solving the problem at hand. Notes: cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@4463ce53 ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@747ece38 Through org.apache.xalan.xsltc.dom.DOMAdapter@3114fa48; Conference Code:83340This paper is focusing on comparing the performance of Differential Evolution (DE) variants, in the light of analyzing their Explorative power on a set of benchmark function. We have chosen fourteen different variants of DE and fourteen benchmark functions grouped by feature: Unimodal Separable, Unimodal NonSeparable, Multimodal Separable and Multimodal NonSeparable. Fourteen variants of DE were implemented and tested on these fourteen functions for the dimension of 30. The explorative power of the variants is evaluated and analyzed by measuring the evolution of population variance, at each generation. This analysis provides insight about the competitiveness of DE variants in solving the problem at hand. Notes: cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@4463ce53 ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@747ece38 Through org.apache.xalan.xsltc.dom.DOMAdapter@3114fa48; Conference Code:83340

Cite this Research Publication : Dr. Jeyakumar G. and Dr. Shunmuga Velayutham C., “Analyzing the Explorative power of Differential Evolution Variants on Different Classes of Problems”, Lecture Notes in Computer Science (LNCS-6466), Springer-Verlag, vol. 6466. pp. 95-102, 2010.

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