Novel Global Harmony Search Algorithm with New Position Updating for Optimization Problems

Abstract

Novel global harmony search algorithm performs better in many engineering optimization problems, but its optimization accuracy is valued to further study. Therefore, a modified version of NGHS algorithm will be proposed to solve some optimization problems. Inspired by differential evolution algorithm mutation operation, stochastic harmony variable is selected and applied in the position updating to enhance the global search capability. Then double evolution operation be used based on a probability control parameter in evolution process, which aim to reduce the probability of algorithm trouble in local optimum value. Compared to some well-known approaches such as HS, IHS, GHS, IHS_MM, IHS_SM, NGHS, all the results demonstrated that the new proposed algorithm has better potential performance.