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01.10.2013 | Methodologies and Application

Self-adaptive, multipopulation differential evolution in dynamic environments

verfasst von: Pavel Novoa-Hernández, Carlos Cruz Corona, David A. Pelta

Erschienen in: Soft Computing | Ausgabe 10/2013

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Abstract

The present work proposes a simple but effective self-adaptive strategy to control the behaviour of a differential evolution (DE) based multipopulation algorithm for dynamic environments. Specifically, the proposed scheme is aimed to control the creation of random individuals by the self-adaptation of the involved parameter. An interaction scheme between random and conventional DE individuals is also proposed and analyzed. The conducted computational experiments show that self-adaptation is profitable, leading to an algorithm that is as competitive as other efficient methods and able to beat the winner of the CEC 2009 competition on dynamic environments.

Vorheriger Artikel Robust adaptive fuzzy control of twin rotor MIMO system

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Although the name of this algorithm suggests the presence of Differential Evolution paradigm, the “DE” of its name is used to denote diversity and efficiency.

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Titel: Self-adaptive, multipopulation differential evolution in dynamic environments
verfasst von: Pavel Novoa-Hernández
Carlos Cruz Corona
David A. Pelta
Publikationsdatum: 01.10.2013
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 10/2013
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-013-1022-x

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