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A Comparative Study of the Grey Wolf Optimizer and Firefly Algorithm in Mathematical Benchmark Functions of the CEC 15 Competition

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Recent Advances of Hybrid Intelligent Systems Based on Soft Computing

Part of the book series: Studies in Computational Intelligence ((SCI,volume 915))

Abstract

The main goal of this paper is to study the performance of two metaheuristics, that are classified as belonging to Swarm Intelligence, when dealing with complex optimization problems. In this case, the Algorithms are the Grey Wolf Optimizer (GWO) algorithm and Firefly Algorithm (FA). In this case study, we are presenting in this paper the Mathematical Benchmark Functions that were given in the IEEE Congress on Evolutionary Computation 2015 (CEC’ 15) competition, in order to compare these popular algorithms.

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Authors and Affiliations

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

    Luis Rodríguez, Oscar Castillo, Mario García & José Soria

Authors
  1. Luis Rodríguez
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  2. Oscar Castillo
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  3. Mario García
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  4. José Soria
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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, Mexico

    Patricia Melin

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

    Oscar Castillo

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

    Janusz Kacprzyk

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Rodríguez, L., Castillo, O., García, M., Soria, J. (2021). A Comparative Study of the Grey Wolf Optimizer and Firefly Algorithm in Mathematical Benchmark Functions of the CEC 15 Competition. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Recent Advances of Hybrid Intelligent Systems Based on Soft Computing. Studies in Computational Intelligence, vol 915. Springer, Cham. https://doi.org/10.1007/978-3-030-58728-4_9

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