Investigation of Performance of HHO Algorithm in Solving Global Optimization Problems

Abstract

In recent years, the use of meta-heuristic optimization algorithms has been increasing in most areas of science and engineering. These algorithms have advantages and disadvantages to each other. In this study, the performance of the Harris hawks optimization (HHO) algorithm has been verified by performing comparative statistical analysis of the optimal solutions of some well-known benchmark functions. Sphere, Rosenbrock, Schwefel, Ackley, Egg Crate and Easom are the chosen benchmark functions that are commonly used. From the analysis results, it is seen that the HHO algorithm were superior to artificial bee colony (ABC), wind driven optimization (WDO) and atom search optimization (ASO) algorithms. In addition, the results of the statistical boxplot prove the unique performance and efficiency of the HHO algorithm. © 2019 IEEE.