An improved variant of the conventional Harmony Search algorithm

The Harmony Search algorithm (HS) has been used for optimization in different fields, and despite the relative short time it has been around, it already has many variants. This article presents a new modification of HS, based on variable parameters, which is able to yield better results than previously reported data, and with the additional benefit of not requiring prior knowledge of the maximum number of iterations. In this research, a comparison is made with the original HS algorithm, and with its improved version (i.e. IHS), finding that the proposed variants not only reduce convergence time of the algorithm, but they also increase its precision. Some commonly used benchmark functions were used as a testing scenario, and the performance of the novel approach is evaluated for an objective function in up to 1000D, where it was found to converge appropriately. These findings are important since they indicate that the proposed version could be used for different kinds of optimization problems, thus allowing a broader use of the HS algorithm.