摘要
介绍了一种新的集群智能算法-微粒群算法(PSO),该算法具有实现简单、参数少且收敛快的特点。针对其易于陷入局部最优的缺陷,文中通过引入遗传算法中的“杂交”算子,并采用自适应的惯性权重,对原算法进行了改进,并将其应用于水库长期优化调度问题。用实际算例验证了该算法的有效性,从而为水库优化调度问题提供了一种新的求解途径。
A new algorithm of swarm intelligence, Particle Swarm Optimization （PSO）, which is an algorithm of simple implementation and fast convergence with few parameters, is introduced in this paper. The conventional PSO is modified through introducing a hybrid operator of GA, and using a self-adaptive inertia weight to avoid premature convergence. The new method is applied in long-term reservoir operation optimization. The effectiveness of this modified PSO is verified by practical application. Therefore, it provides a new method for reservoir operation optimization.
出处
《中国农村水利水电》
北大核心
2006年第2期54-56,共3页
China Rural Water and Hydropower
关键词
微粒群算法(PSO)
水库优化调度
长期调度
particle swarm optimization（PSO）
reservoir operation optimization
long-term operation
