A novel hybrid particle swarm optimization algorithm combined with harmony search for high dimensional optimization problems

Particle swarm optimization (PSO) has gained increasing attention in tackling optimization problems. Its further superiority when hybridized with other techniques is also shown. In this paper a novel hybrid particle swarm optimization (NHPSO) is proposed in order to solve high dimensional optimization problems more efficiently, accurately and reliably. It provides a new architecture of hybrid algorithms, which organically merges the harmony search (HS) method into particle swarm optimization (PSO). During the course of evolvement, harmony search is used to improve the search performance and this makes NHPSO algorithm have more powerful exploitation capabilities. Simulation and comparisons based on several well-studied benchmarks demonstrate the effectiveness, efficiency and robustness of the proposed NHPSO.