An adaptive differential evolution algorithm with an aging leader and challengers mechanism

[Display omitted] An adaptive differential evolution algorithm with an aging leader and challengers mechanism, called ADE-ALC, is proposed to solve optimization problems. In ADE-ALC algorithm, the aging mechanism is introduced into the framework of differential evolution to maintain diversity of the...

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Bibliographic Details
Published inApplied soft computing Vol. 57; pp. 60 - 73
Main Authors Fu, C.M., Jiang, C., Chen, G.S., Liu, Q.M.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.08.2017
Subjects
Adaptive parameter control
Aging leader
Differential evolution
Evolutionary algorithms
Global optimization
Differential evolution
Global optimization
Adaptive parameter control
Aging leader
Evolutionary algorithms
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Summary:[Display omitted] An adaptive differential evolution algorithm with an aging leader and challengers mechanism, called ADE-ALC, is proposed to solve optimization problems. In ADE-ALC algorithm, the aging mechanism is introduced into the framework of differential evolution to maintain diversity of the population. The key control parameters are adaptively updated based on given probability distributions which could learn from their successful experiences to generate the promising parameters at the next generation. One of the two local search operators is randomly selected to generate challengers which are beneficial for increasing the diversity of population. Finally, the effectiveness of the ADE-ALC algorithm is verified by the numerical results of twenty-five benchmark test functions.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2017.03.032