Improved chaotic particle swarm optimization based on function transform
基于函数变换的改进混沌粒子群优化

Particle swarm optimization was easily trapped by the local optima and failed to find the global optima.To solve this premature problem,introduced the logistic map and the improved Tent map into the PSO to replace the randomness.Applied function transform to refine the searching in the updating process of particle velocity and particle position. The difference between the local optima and global optima is more obvious, which leads the particle jump out the trap and find the global optima. The numerical experiment shows that the chaotic PSO based on improved Tent map has a better searching result than the standard PSO and chaotic PSO based on logistic map. And the improved algorithm is feasible and effective.