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Nature-Inspired Design of Hybrid Intelligent Systems pp 257–268Cite as

Differential Evolution Using Fuzzy Logic and a Comparative Study with Other Metaheuristics

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 667))

Abstract

This paper proposes an improvement to the algorithm differential evolution (DE) using fuzzy logic. The main contribution of this work is to dynamically adapt the parameter of mutation (F) using a fuzzy system, with the aim that the fuzzy system calculates the optimal parameters of the DE algorithm for obtaining better solutions, in this way arriving to the proposed new fuzzy differential evolution (FDE) algorithm. In this paper, experiments are performed with a set of mathematical functions using the proposed method to show the advantages of the FDE algorithm.

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Authors and Affiliations

  1. Tijuana Institute of Technology, Tijuana, Mexico

    Patricia Ochoa, Oscar Castillo & José Soria

Authors
  1. Patricia Ochoa
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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. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, BC, Mexico

    Patricia Melin

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, BC, Mexico

    Oscar Castillo

  3. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

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Ochoa, P., Castillo, O., Soria, J. (2017). Differential Evolution Using Fuzzy Logic and a Comparative Study with Other Metaheuristics. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Nature-Inspired Design of Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 667. Springer, Cham. https://doi.org/10.1007/978-3-319-47054-2_17

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  • DOI: https://doi.org/10.1007/978-3-319-47054-2_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-47053-5

  • Online ISBN: 978-3-319-47054-2

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