Abstract
Differential evolution (DE) has been shown to be a simple, yet powerful, evolutionary algorithm for global optimization for many real problems. Adaptation, especially self-adaptation, has been found to be highly beneficial for adjusting control parameters, especially when done without any user interaction. This paper presents differential evolution algorithms, which use different adaptive or self-adaptive mechanisms applied to the control parameters. Detailed performance comparisons of these algorithms on the benchmark functions are outlined.
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Brest, J., Bošković, B., Greiner, S. et al. Performance comparison of self-adaptive and adaptive differential evolution algorithms. Soft Comput 11, 617–629 (2007). https://doi.org/10.1007/s00500-006-0124-0
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DOI: https://doi.org/10.1007/s00500-006-0124-0