An adaptive hybrid combination of PSO and Extremal Optimization

Particle Swarm Optimization (PSO) has proved to be an effective global optimization in recent years. However, PSO still suffers from the prematurity to local optima. In order to solve this disadvantage, researches have carried out by combination with other optimizers. In recent years, a local optimization called Extremal Optimization (EO) has been introduced into PSO and gain improvements. Although, the combination of PSO with EO would bring severe computation overhead result in the simple way they combined. In this paper, an adaptive hybrid combined PSO (AHPSO-EO) is proposed. It can improve the computation effectively by an adaptive way. The experimental results on benchmark functions reveal that the adaptive PSO combined with EO accelerates the convergence and improves the performance of proposed algorithm.