A modified particle swarm optimization
Zhigang Wang · Journal of Harbin University of Commerce · 2009
Particle swarm optimization is a new computational method for tackling optimization functions.However,it is easily trapped into the local optimization when solving high-dimension functions.To overcome this shortcoming,a new particle swarm optimization which improves particle's velocity and position update rule to adjust its movement based on the individual best position is proposed in the paper.The modified algorithm can enhance capability of optimization.Five benchmark functions are tested,and the results indicate that the modified particle swarm optimization is effective to find the global optimal solution.