Mechanism of Particle Swarm Optimization and Analysis on Its Convergence

Particle swarm optimization (PSO) is a new swarm intelligence algorithm, derived from artificial life and evolutionary computation theory. It makes full use of the information-sharing particles of the cluster to obtain the optimal solution of the evolution from disorder to orderliness. It has received great concern because of its simple calculation forms, parameter settings and a good convergence of the algorithm. But there is no given mathematical proof of the algorithm convergence and convergence rate. Therefore this paper is designed to analyze the ion swarm optimization principles, expound the process of algorithm convergence and introduce the PSO to meet the convergence under the great changes of population diversity.