基于适应值引导的粒子群改进算法

摘要

Particle Swarm Optimization(PSO), as a kind of intelligent algorithm, is widely applied to various fields. Through comparing with several common particle swarm optimization, this paper proposes PSO based on fitness direc-tion, in order to increase the diversity of particle swarm, then speeds up convergence. Compared with other algorithm, experi-mental results show improved PSO based on fitness direction performs well on the rate of convergence and the conver-gence speed.%粒子群算法是一种智能算法，被广泛用于各领域。通过比较几类常见的粒子群算法的优劣，提出了基于适应值引导的粒子群算法，以增加粒子群的多样性，从而加快收敛速度。实验结果证明，与其他算法相比，基于适应值引导的粒子算法的收敛率与收敛速度表现最佳。