Harmony search algorithm with dynamic control parameters

Harmony search (HS) is a population-based meta-heuristic imitating the music improvisation process, which has been successfully applied to optimization problems in recent years. This paper presents an effective harmony search algorithm for solving global continuous optimization problems. The proposed method presents a novel improvisation process which is different from the classical HS in two aspects. Firstly, the candidate harmony is chosen from the harmony memory by a tournament selection rule, so that the harmonies with better fitness will have more opportunities to be used in generating new harmonies. Secondly, two key control parameters, pitch adjustment rate (PAR) and bandwidth distance (bw), are adjusted dynamically with respect to the evolution of the search process and the different search spaces of the optimization problems. Numerical results demonstrate that the proposed algorithm performs much better than the existing HS variants in terms of the solution quality and the stability.