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Galactic Swarm Optimization with Adaptation of Parameters Using Fuzzy Logic for the Optimization of Mathematical Functions

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Book cover Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 749))

Abstract

In this paper the Galactic Swarm Optimization (GSO) algorithm with the use of fuzzy systems for the adaptation of the parameters in the GSO algorithm is proposed. This algorithm is inspired by the movement of stars, galaxies and superclusters of galaxies under the force of gravity. The GSO algorithm uses multiple cycles of exploration and exploitation phases to achieve a balance between exploring new solutions and exploiting existing solutions. In this work different fuzzy systems were designed for the dynamic adaptation of the c3 and c4 parameters to measure the operation of the algorithm with 7 mathematical functions with different number of dimensions. A statistical comparison was made between the different variants to test the performance of the method applied to optimization problems.

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Acknowledgements

We would like to express our gratitude to the CONACYT and Tijuana Institute of Technology for the facilities and resources granted for the development of this research.

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Authors and Affiliations

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

    Emer Bernal, Oscar Castillo, José Soria & Fevrier Valdez

Authors
  1. Emer Bernal
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  2. Oscar Castillo
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  3. José Soria
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  4. Fevrier Valdez
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Corresponding author

Correspondence to Oscar Castillo .

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Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

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

    Patricia Melin

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

    Janusz Kacprzyk

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Bernal, E., Castillo, O., Soria, J., Valdez, F. (2018). Galactic Swarm Optimization with Adaptation of Parameters Using Fuzzy Logic for the Optimization of Mathematical Functions. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications. Studies in Computational Intelligence, vol 749. Springer, Cham. https://doi.org/10.1007/978-3-319-71008-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-71008-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71007-5

  • Online ISBN: 978-3-319-71008-2

  • eBook Packages: EngineeringEngineering (R0)

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