A comparative study on the performance of Gray Wolves Optimization and Multi-Free Dynamic Schema

Abstract

In this paper, we present a comparison study on the performance of Gray Wolves Optimization (GWO) and Multi-free dynamic schema (MFDS) algorithms. The Multi-free Dynamic Schema (MFDS) algorithm is a sophisticated optimization method created for solving optimization problems. It contains different operators (dynamic schema operator, dissimilarity operator, similarity operator and free dynamic schema operator). Where, The Grey Wolf Optimization (GWO) algorithm is a metaheuristic optimization algorithm inspired by the social behavior of grey wolves in a pack. This study focused on the run time and the number of iterations to reach the optimal solutions. The sample of this comparison was on ten functions. The results showed the superiority of an algorithm (MFDS) on (GWO) algorithm in most test functions, especially at the run time.