Abstract

This paper provides a detailed overview of the Grey Wolf Optimizer (GWO).The social hunting behaviour of grey wolves served as the inspiration for the recently introduced meta-heuristic known as the GWO algorithm. The GWO has been employed in almost all optimization areas and engineering practice and it has grown more and more important as a tool of swarm intelligence. The GWO algorithm and its variations have successfully shed light on several difficulties from various fields. The original GWO algorithm needed to be altered or hybridized in order to be used to reveal various challenges. This paper undertakes a thorough analysis of this active and developing field of swarm intelligence in order to demonstrate how the GWO algorithm may be related to every problem that arises in practice. However, it enables less experienced researchers and algorithm makers to use this simple but incredibly powerful method for problem solving. It frequently makes sure that the results obtained will live up to expectations.