A comparative study of dynamic adaptation of parameters in the GWO algorithm using type-1 and interval type-2 fuzzy logic

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.