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A Comparative Study of Dynamic Adaptation of Parameters in the GWO Algorithm Using Type-1 and Interval Type-2 Fuzzy Logic

  • Luis Rodríguez
  • Oscar CastilloEmail author
  • Mario García
  • José Soria
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 749)

Abstract

The main goal of this paper is to present a comparative study of dynamic adjustment of parameters in the Grey Wolf Optimizer algorithm using type-1 and interval type-2 fuzzy logic respectively. We proposed the fuzzy inference system for both types of fuzzy logic and we present the performance of these proposed methods with a set of 13 benchmark functions that we are presenting in this paper.

Keywords

Grey wolf optimizer Fuzzy logic Interval type-2 Benchmark functions Dynamic Optimization 

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Luis Rodríguez
    • 1
  • Oscar Castillo
    • 1
    Email author
  • Mario García
    • 1
  • José Soria
    • 1
  1. 1.Tijuana Institute of TechnologyTijuanaMexico

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