research-article

Improving differential evolution algorithm by synergizing different improvement mechanisms

Authors:

Ajith AbrahamAuthors Info & Claims

ACM Transactions on Autonomous and Adaptive Systems (TAAS), Volume 7, Issue 2

Article No.: 20, Pages 1 - 32

https://doi.org/10.1145/2240166.2240170

Published: 30 July 2012 Publication History

Abstract

Differential Evolution (DE) is a well-known Evolutionary Algorithm (EA) for solving global optimization problems. Practical experiences, however, show that DE is vulnerable to problems like slow and/or premature convergence. In this article we propose a simple and modified DE framework, called MDE, which is a fusion of three recent modifications in DE: (1) Opposition-Based Learning (OBL); (2) tournament method for mutation; and (3) single population structure. These features have a specific role which helps in improving the performance of DE. While OBL helps in giving a good initial start to DE, the use of the tournament best base vector in the mutation phase helps in preserving the diversity. Finally the single population structure helps in faster convergence. Their synergized effect balances the exploitation and exploration capabilities of DE without compromising with the solution quality or the convergence rate. The proposed MDE is validated on a set of 25 standard benchmark problems, 7 nontraditional shifted benchmark functions proposed at the special session of CEC2008, and three engineering design problems. Numerical results and statistical analysis show that the proposed MDE is better than or at least comparable to the basic DE and several other state-of-the art DE variants.

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Improving differential evolution algorithm by synergizing different improvement mechanisms

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cover image ACM Transactions on Autonomous and Adaptive Systems

ACM Transactions on Autonomous and Adaptive Systems Volume 7, Issue 2

July 2012

275 pages

ISSN:1556-4665

EISSN:1556-4703

DOI:10.1145/2240166

Issue’s Table of Contents

Copyright © 2012 ACM.

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Publication History

Published: 30 July 2012

Accepted: 01 March 2011

Revised: 01 November 2010

Received: 01 June 2010

Published in TAAS Volume 7, Issue 2

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https://doi.org/10.3390/en15082944
Wang HZhen XTu XYaacoub C(2019)SFDEWireless Communications & Mobile Computing10.1155/2019/29650612019Online publication date: 4-Mar-2019
https://dl.acm.org/doi/10.1155/2019/2965061
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https://dl.acm.org/doi/10.1016/j.cageo.2013.09.007
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