Hybrid ensemble PSO-GSO algorithm

A hybrid swarm optimization algorithm is presented which combines particle swarm optimization (PSO) with glowworm swarm optimization (GSO) and in which ensemble learning is used to synthesize the final population. PSO can converge quickly but always falls into premature problem, while GSO is easy to capture many peaks of multimodal function due to its dynamic sub-groups but also easy to be trapped in problems of low convergence and low precision. Combining the two algorithms can balance the diversity and convergence. And ensemble learning could achieve a more accurate position. Experiment results are examined with benchmark functions and results show that the proposed hybrid algorithm outperforms many versions of PSO.