Adaptive harmony search with best-based search strategy

Harmony search (HS) is a new evolutionary algorithm inspired by the process of music improvisation. During the past decade, HS has shown excellent performance in many fields. However, its search strategy often demonstrates insufficient exploitation ability when facing some complex practical problems. Moreover, the HS performance is significantly influenced by its control parameters. To enhance the search efficiency, an adaptive harmony search with best-based search strategy (ABHS) is proposed. In the search process, ABHS exploits the beneficial information from the global-best solution to improve the search ability, while it adaptively tunes its control parameters according to the feedback from the search process. Experiments are conducted on a set of classical test functions. The experimental results show that ABHS significantly enhances the search efficiency of HS.