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Controlled Refresh of the Population in Differential Evolution for Real-World Problems

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Artificial Intelligence and Soft Computing (ICAISC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14125))

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Abstract

In this paper, a new variant of the Differential Evolution (DE) algorithm is proposed to control the diversity of individuals in the population. The proposed approach is based on the failure of individuals in successive generations. The positions of the unsuccessful individuals are refreshed by employing the position parameters of the successful individuals from the population. Two control parameters of the proposed approach are studied to eliminate inappropriate settings. These nine variants of newly designed DE variants are compared with the classic DE algorithm when solving the set of real-world problems CEC 2011. The results show a very promising ability to solve real-world problems when the DE uses the proposed mechanism with the appropriate settings.

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References

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Authors and Affiliations

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

    Petr Bujok, Martin Lacko & Patrik Kolenovský

Authors
  1. Petr Bujok
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  2. Martin Lacko
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  3. Patrik Kolenovský
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Corresponding author

Correspondence to Petr Bujok .

Editor information

Editors and Affiliations

  1. Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland

    Leszek Rutkowski

  2. Częstochowa University of Technology, Częstochowa, Poland

    Rafał Scherer

  3. Częstochowa University of Technology, Częstochowa, Poland

    Marcin Korytkowski

  4. University of Alberta, Edmonton, AB, Canada

    Witold Pedrycz

  5. AGH University of Krakow, Kraków, Poland

    Ryszard Tadeusiewicz

  6. University of Louisville, Louisville, KY, USA

    Jacek M. Zurada

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Bujok, P., Lacko, M., Kolenovský, P. (2023). Controlled Refresh of the Population in Differential Evolution for Real-World Problems. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2023. Lecture Notes in Computer Science(), vol 14125. Springer, Cham. https://doi.org/10.1007/978-3-031-42505-9_30

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  • DOI: https://doi.org/10.1007/978-3-031-42505-9_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-42504-2

  • Online ISBN: 978-3-031-42505-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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