摘要
粒子群优化算法是一种新型的演化算法,概念简单,参数较少,易于实现,但粒子群算法易陷入局部最优导致收敛变慢。寻求解决实际问题的更加有效的粒子群优化算法是论文研究的目标。论文对粒子群算法的算法参数、拓扑结构及混合算法等方面的改进措施进行了概述,并对粒子群算法进行了展望。
Particle swarm optimization is a new evolutionary algorithm. It is simple in concept, and it has few parameters and is easy to implement. The goal of this paper is to find a more effective particle swarm optimization algorithm to solve practical problems. In this paper, the improvement measures of particle swarm optimization are summarized, including the algorithm parameters, topology and hybrid algorithm.
作者
吴玫
WU Mei(Jiangsu Urban and Rural Construction Vocational College, Changzhou 213002, China)
出处
《中小企业管理与科技》
2018年第36期167-168,共2页
Management & Technology of SME
关键词
粒子群算法
算法参数
拓扑结构
混合算法
particle swarm algorithm
algorithm parameter
topology
hybrid algorithm
