A Harmony Search Algorithm with Ensemble of Parameter Sets

This paper presents a harmony search algorithm with ensemble of parameter sets, named EHS algorithm, for solving continuous optimization problems. In the proposed algorithm, an ensemble of parameter sets is adopted to self-adaptively choose the best control parameters during the evolution process. This method not only eliminates the need to perform the trail-and-error search for the best single parameter set, but enables us to benefit from the match between the parameter sets, the different search phases, and the specific problems as well. Extensive computational simulations and comparisons are carried out by employing a set of 10 benchmark problems from the literature. The computational results show that the proposed EHS algorithm is more effective in finding better solutions than the state-of-the-art harmony search (HS) variants [1,2,3].