A novel particle swarm optimization algorithm

Abstract

A novel particle swarm optimization (NPSO) algorithm with dynamically changing inertia weight based on fltness and iterations was presented for improving the performance of the Particle Swarm Optimization algorithm. The new algorithm was tested with three benchmark functions. The experimental results show that the swarm can escape from local optimum, and it also can speed up the convergence of particles to improve the performance.