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Fuzzy Logic in Dynamic Parameter Adaptation of Harmony Search Optimization for Benchmark Functions and Fuzzy Controllers

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Abstract

Nowadays the use of fuzzy logic has been increasing in popularity, and this is mainly due to the inference mechanism that allows simulating human reasoning in knowledge-based systems. The main contribution of this work is using the concepts of fuzzy logic in a method for dynamically adapting the main parameters of the harmony search algorithm during execution. Dynamical adaptation of parameters in metaheuristics has been shown to improve performance and accuracy in a wide range of applications. For this reason, we propose and approach for fuzzy adaptation of parameters in harmony search. Two case studies are considered for testing the proposed approach, the optimization of mathematical functions, which are unimodal, multimodal, hybrid, and composite functions and a control problem without noise and when noise is considered. A statistical comparison between the harmony search algorithm and the fuzzy harmony search algorithm is presented to verify the advantages of the proposed approach.

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Acknowledgements

We thank the Division of Graduate Studies and Research of Tijuana Institute of Technology and the financial support provided by CONACYT contract grant Number: 122.

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Authors and Affiliations

  1. Tijuana Institute of Technology, 22379, Tijuana, Mexico

    Fevrier Valdez, Oscar Castillo & Cinthia Peraza

Authors
  1. Fevrier Valdez
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  2. Oscar Castillo
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  3. Cinthia Peraza
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Contributions

FV analyzed the results and did investigation; OC conceived of the presented approach and developed the framework of this study, including methodology; CP carried out the simulations and wrote the article. All authors discussed the results and contributed to the final manuscript.

Corresponding author

Correspondence to Oscar Castillo.

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The authors declare no conflict of interest.

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Valdez, F., Castillo, O. & Peraza, C. Fuzzy Logic in Dynamic Parameter Adaptation of Harmony Search Optimization for Benchmark Functions and Fuzzy Controllers. Int. J. Fuzzy Syst. 22, 1198–1211 (2020). https://doi.org/10.1007/s40815-020-00860-7

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  • DOI: https://doi.org/10.1007/s40815-020-00860-7

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