Harmony search algorithm and related variants: a systematic review

Abstract

Harmony search (HS) algorithm is a novel metaheuristic algorithm, inspired by the phenomenon that musicians repeatedly adjust the pitch of each instrument to finally achieve a beautiful harmony state. Due to its simple concept, few adjustable parameters, easy implementation, and the ability to balance exploitation and exploration during search, HS has been widely applied to deal with various optimization problems in real life. However, HS has shortcomings such as low optimization accuracy and premature convergence. Therefore, various HS variants have been proposed. In response to this trend, this article systematically reviews HS and its variants from various aspects. First, the basic HS principle is described. Secondly, how the improvement of HS affects the performance of the algorithm is discussed. Finally, the characteristics of HS variants and their applications are analyzed. It can be seen from the literature that the improvement of HS is mainly focused on parameter improvement and mixing with other metaheuristic algorithms. Some HS even use both techniques to improve the algorithm simultaneously. HS is mainly used to solve optimization problems in engineering, which provides future research directions for improving HS.