Optimal combination for multi-objective Particle Swarm Optimization

One fundamental challenge for the problems of the traditional Particle Swarm Optimization is convergence too fast, also particles are easy to fall into premature, in addition that. it always get in the local optimum easily. This paper presents a new and improved Particle Swarm Optimization algorithm, unlike the existing PSO, we improved this optimization from two aspects. In the one hands, this paper proposes a new change to optimization based on the force of changed particles in electric field, whose combination will be more efficiency. In an another hands, for the local optimization phenomenon in tradition PSO, this paper use a hierarchical search algorithm :niche algorithm. Through simulation numerical tests show that the method of the model can improve the accuracy and the optimization capability.