An improved particle swarm optimization algorithm based on velocity updating

The particle swarm optimization is a stochastic optimization technique for finding optimal regions of complex problems through the interaction of individuals in the swarm. In this paper the search trajectory of particle is analyzed. Based on the behavior of each particle, the factors which affect the convergence and the convergence rate are discussed. Furthermore, an improved particle swarm optimization algorithm is proposed based on the new velocity updating equation. The new algorithm is applied to some benchmark problems, the numerical experiments show that the new algorithm has better performance than the standard PSO and PSO with inertia weight.