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A Study of Parameter Dynamic Adaptation with Fuzzy Logic for the Grey Wolf Optimizer Algorithm

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Advances in Computational Intelligence (MICAI 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10061))

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Abstract

The main goal of this paper is to present a general study of the Grey Wolf Optimizer algorithm. We perform tests to determine in the first part which parameters are candidates to be dynamically adjusted and in the second stage to determine which are the parameters that have the greatest effect in the performance of the algorithm. We also present a justification and results of experiments as well as the benchmark functions that were used for the tests that are presented. In addition we are presenting a simple fuzzy system with the results obtained based on this general study.

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Author information

Authors and Affiliations

  1. Tijuana Institute of Technology, Tijuana, Mexico

    Luis Rodríguez, Oscar Castillo & José Soria

Authors
  1. Luis Rodríguez
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  2. Oscar Castillo
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  3. José Soria
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Corresponding author

Correspondence to Oscar Castillo .

Editor information

Editors and Affiliations

  1. Instituto Politécnico Nacional, Centro de Investigación en Computación, Mexico City, Mexico

    Grigori Sidorov

  2. Universidad Autónoma Metropolitana, Mexico City, Mexico

    Oscar Herrera-Alcántara

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Rodríguez, L., Castillo, O., Soria, J. (2017). A Study of Parameter Dynamic Adaptation with Fuzzy Logic for the Grey Wolf Optimizer Algorithm. In: Sidorov, G., Herrera-Alcántara, O. (eds) Advances in Computational Intelligence. MICAI 2016. Lecture Notes in Computer Science(), vol 10061. Springer, Cham. https://doi.org/10.1007/978-3-319-62434-1_19

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  • DOI: https://doi.org/10.1007/978-3-319-62434-1_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62433-4

  • Online ISBN: 978-3-319-62434-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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