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Self-adaptive, multipopulation differential evolution in dynamic environments
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DOI：10.1007/s00500-013-1022-x.png)
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摘要
En 中文
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.
Keyword:
Differential evolution
Self-adaptation
Dynamic environments
期刊
IF:
2.5
论文数:
1.0W
被引数:
2.1W
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