A study of parameter dynamic adaptation with fuzzy logic for the Grey Wolf optimizer algorithm

Abstract

The main goal of this paper is to present a general study of the Grey Wolf Optimizer algorithm. We perform tests to determine in the first part which parameters are candidates to be dynamically adjusted and in the second stage to determine which are the parameters that have the greatest effect in the performance of the algorithm. We also present a justification and results of experiments as well as the benchmark functions that were used for the tests that are presented. In addition we are presenting a simple fuzzy system with the results obtained based on this general study.