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On the Performance and Complexity of Crossover in Differential Evolution Algorithm

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Artificial Intelligence and Soft Computing (ICAISC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12415))

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Abstract

In this study, the efficiency and complexity of four different crossover variants in Differential evolution (DE) algorithm are experimentally studied. Three well-known crossover variants with a newly designed crossover are applied in nine state-of-the-art and one standard DE algorithm. The results obtained from CEC 2011 real-world problems showed a significant difference between different DE variants and crossover types in performance and time complexity. Higher time complexity is for Eigen crossover, higher efficiency s for newly designed crossover.

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Author information

Authors and Affiliations

  1. University of Ostrava, 30. dubna 22, 70200, Ostrava, Czech Republic

    Petr Bujok

Authors
  1. Petr Bujok
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Correspondence to Petr Bujok .

Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Częstochowa, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Science and Technology, Kraków, Poland

    Ryszard Tadeusiewicz

  6. Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Bujok, P. (2020). On the Performance and Complexity of Crossover in Differential Evolution Algorithm. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2020. Lecture Notes in Computer Science(), vol 12415. Springer, Cham. https://doi.org/10.1007/978-3-030-61401-0_34

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  • DOI: https://doi.org/10.1007/978-3-030-61401-0_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61400-3

  • Online ISBN: 978-3-030-61401-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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