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Performance comparison of self-adaptive and adaptive differential evolution algorithms

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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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Authors and Affiliations

  1. Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia

    Janez Brest, Borko Bošković, Sašo Greiner, Viljem Žumer & Mirjam Sepesy Maučec

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  1. Janez Brest
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  2. Borko Bošković
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  3. Sašo Greiner
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  4. Viljem Žumer
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  5. Mirjam Sepesy Maučec
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Correspondence to Janez Brest.

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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

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