Fuzzy Combination of Moth-Flame Optimization and Lightning Search Algorithm with Fuzzy Dynamic Parameter Adjustment

Authors

  • Yunkio Kawano Instituto Tecnológico de Tijuana
  • Fevrier Valdez Instituto Tecnológico de Tijuana
  • Oscar Castillo Instituto Tecnológico de Tijuana

DOI:

https://doi.org/10.13053/cys-26-2-4269

Keywords:

Swarm intelligence algorithms, fuzzy logic systems, migration

Abstract

In general, this paper is focused on creating a fuzzy combination of two optimization algorithms. In this case, the algorithms work with populations and allow us to migrate between them every certain number of iterations. On the other hand, fuzzy logic is responsible for the dynamic adjustment of parameters within each of the algorithms since the variables are different in each algorithm. In previous works, a combination between genetic algorithm and particle swarm optimization was developed, which motivated us to create this combination expecting to obtain better results when compared to the previous works. The moth-flame optimization and lightning search algorithm were combined to obtain a powerful hybrid metaheuristic combining the advantages of both individual algorithms.

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Published

2022-06-15

Issue

Vol. 26 No. 2 (2022): Emerging Issues and Applications of Fuzzy Systems, Neural Networks and Metaheuristics (Castillo, Melin, Montiel, Valdez)

Section

Articles of the Thematic Issue

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