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Dynamic group-based differential evolution using a self-adaptive strategy for global optimization problems

Authors:

Jyh-Yeong Chang,

Chin-Teng LinAuthors Info & Claims

Applied Intelligence, Volume 39, Issue 1

Pages 41 - 56

https://doi.org/10.1007/s10489-012-0393-5

Published: 01 July 2013 Publication History

Abstract

This paper describes a dynamic group-based differential evolution (GDE) algorithm for global optimization problems. The GDE algorithm provides a generalized evolution process based on two mutation operations to enhance search capability. Initially, all individuals in the population are grouped into a superior group and an inferior group based on their fitness values. The two groups perform different mutation operations. The local mutation model is applied to individuals with better fitness values, i.e., in the superior group, to search for better solutions near the current best position. The global mutation model is applied to the inferior group, which is composed of individuals with lower fitness values, to search for potential solutions. Subsequently, the GDE algorithm employs crossover and selection operations to produce offspring for the next generation. In this paper, an adaptive tuning strategy based on the well-known 1/5th rule is used to dynamically reassign the group size. It is thus helpful to trade off between the exploration ability and the exploitation ability. To validate the performance of the GDE algorithm, 13 numerical benchmark functions are tested. The simulation results indicate that the approach is effective and efficient.

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Published In

cover image Applied Intelligence

Applied Intelligence Volume 39, Issue 1

July 2013

216 pages

ISSN:0924-669X

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Copyright © Copyright © 2013 Springer Science+Business Media New York.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 July 2013

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Cited By

Crawford BSoto ROlivares REmbry GFlores DPalma WCastro CParedes FRubio J(2019)A binary monkey search algorithm variation for solving the set covering problemNatural Computing: an international journal10.1007/s11047-019-09752-819:4(825-841)Online publication date: 11-Jul-2019
https://dl.acm.org/doi/10.1007/s11047-019-09752-8
Sun GXu GJiang N(2019)A simple differential evolution with time-varying strategy for continuous optimizationSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-019-04159-024:4(2727-2747)Online publication date: 24-Jun-2019
https://dl.acm.org/doi/10.1007/s00500-019-04159-0
Feng XXu HWang YYu H(2019)The social team building optimization algorithmSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-018-3303-x23:15(6533-6554)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s00500-018-3303-x
Chen JCai HWang W(2018)A new metaheuristic algorithmSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-017-2845-722:12(3857-3878)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1007/s00500-017-2845-7
Sun GPeng JZhao R(2018)Differential evolution with individual-dependent and dynamic parameter adjustmentSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-017-2626-322:17(5747-5773)Online publication date: 1-Sep-2018
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Parouha RDas K(2016)DPDExpert Systems with Applications: An International Journal10.1016/j.eswa.2016.07.01263:C(295-309)Online publication date: 30-Nov-2016
https://dl.acm.org/doi/10.1016/j.eswa.2016.07.012
Sun GZhao RLan Y(2016)Joint operations algorithm for large-scale global optimizationApplied Soft Computing10.1016/j.asoc.2015.10.04738:C(1025-1039)Online publication date: 1-Jan-2016
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Parouha RDas K(2015)An efficient hybrid technique for numerical optimization and applicationsComputers and Industrial Engineering10.1016/j.cie.2015.02.01083:C(193-216)Online publication date: 1-May-2015
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Yi WGao LLi XZhou Y(2015)A new differential evolution algorithm with a hybrid mutation operator and self-adapting control parameters for global optimization problemsApplied Intelligence10.1007/s10489-014-0620-342:4(642-660)Online publication date: 1-Jun-2015
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