Comparative Study of Metaheuristic Methods Inspired by the Prey House Mechanism

Currently there is a set of techniques for solving complex problems known as NP-Hard, these problems have the characteristic that there are no exact procedures to solve them in polynomial time, so methods known as metaheuristics are used. Metaheuristic methods are methods that solve complex problems in a reasonable time and with useful solutions. There are different metaheuristics that can be used to solve problems, one category that has emerged recently are the algorithms based on swarm intelligence. Within these metahuristics it is possible to find methods inspired by the hunting behaviors of different animals in nature. This article evaluates the performance of three metaheuristic methods inspired by the hunting behavior of different animals. The metaheuristic methods considered in this work are: Cheetah Optimizer (CO) [1], Whale Optimization Algorithm (WOA) [2], and Gray Wolf Optimization (GWO) [3]. The performance was evaluated by means of 23 different functions divided into three types: unimodal, multimodal, and fixed dimension multimodal functions. The study shows a better exploitation capacity for the GWO algorithm while the CO algorithm has more capacity for exploration.