Self-adaptive, multipopulation differential evolution in dynamic environments


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.

DOI: 10.1007/s00500-013-1022-x

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@article{NovoaHernndez2013SelfadaptiveMD, title={Self-adaptive, multipopulation differential evolution in dynamic environments}, author={Pavel Novoa-Hern{\'a}ndez and Carlos Cruz Corona and David A. Pelta}, journal={Soft Comput.}, year={2013}, volume={17}, pages={1861-1881} }