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01-10-2013 | Methodologies and Application

Self-adaptive, multipopulation differential evolution in dynamic environments

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

Published in: Soft Computing | Issue 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.

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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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Title: Self-adaptive, multipopulation differential evolution in dynamic environments
Authors: Pavel Novoa-Hernández
Carlos Cruz Corona
David A. Pelta
Publication date: 01-10-2013
Publisher: Springer Berlin Heidelberg
Published in: Soft Computing / Issue 10/2013
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-013-1022-x

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