The Performance Analysis of Particle Swarm Optimization for Solving Continuous Optimization Problem

Particle swarm algorithm is a stochastic global optimization technique and it is fit for function optimization.The particle swarm algorithm find optimal regions of complex search spaces through the interaction of individuals in a population of particles.In this paper,classical particle swarm optimization algorithm is introduced.Furthermore results of experiments on three benchmark functions are shown and they demonstrate the efficiency of PSO in different ways.