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Neural-Network Based Adaptation of Variation Operators’ Parameters for Metaheuristics

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Computational Science – ICCS 2022 (ICCS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13351))

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Abstract

The paper presents an idea of training an artificial neural network a relation between different parameters observed for a population in a metaheuristic algorithm. Then such trained network may be used for controlling other algorithms (if the network is trained in such way, that the knowledge gathered by it becomes agnostic regarding the problem). The paper focuses on showing the idea and also provides selected experimental results obtained after applying the proposed algorithm for solving popular benchmark problems in different dimensions.

The research presented in this paper has been financially supported by: Polish National Science Center Grant no. 2019/35/O/ST6/00570 “Socio-cognitive inspirations in classic metaheuristics.” (A.U.) and Polish Ministry of Education and Science funds assigned to AGH University of Science and Technology (T.P-P., M.K-D., A.B.).

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Authors and Affiliations

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

    Tymoteusz Dobrzański, Aleksandra Urbańczyk, Tomasz Pełech-Pilichowski, Marek Kisiel-Dorohinicki & Aleksander Byrski

Authors
  1. Tymoteusz Dobrzański
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  2. Aleksandra Urbańczyk
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  3. Tomasz Pełech-Pilichowski
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  4. Marek Kisiel-Dorohinicki
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  5. Aleksander Byrski
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Corresponding author

Correspondence to Aleksander Byrski .

Editor information

Editors and Affiliations

  1. Brunel University London, London, UK

    Derek Groen

  2. University of Amsterdam, Amsterdam, The Netherlands

    Clélia de Mulatier

  3. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  4. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  5. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  6. University of Amsterdam, Amsterdam, The Netherlands

    Peter M. A. Sloot

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Dobrzański, T., Urbańczyk, A., Pełech-Pilichowski, T., Kisiel-Dorohinicki, M., Byrski, A. (2022). Neural-Network Based Adaptation of Variation Operators’ Parameters for Metaheuristics. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13351. Springer, Cham. https://doi.org/10.1007/978-3-031-08754-7_47

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  • DOI: https://doi.org/10.1007/978-3-031-08754-7_47

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  • Print ISBN: 978-3-031-08753-0

  • Online ISBN: 978-3-031-08754-7

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