A modified particle swarm optimization algorithm

Abstract

A modified particle swarm optimization (MPSO) algorithm is presented based on the variance of the population's fitness. During computing, the inertia weight of MPSO is determined adaptively and randomly according to the variance of the population's fitness. And the ability of particle swarm optimization algorithm (PSO) to break away from the local optimum is greatly improved. The simulating results show that this algorithm not only has great advantage of convergence property over standard simple PSO, but also can avoid the premature convergence problem effectively. © 2005 IEEE.