摘要
粒子群优化算法(PSO)是一类基于群体智能的新型全局优化方法,近年来其离散化形式和方法受到广泛关注。介绍了PSO的基本原理和更新机制,论述了离散PSO算法的研究进展和应用情况,详细介绍了两种离散化策略的机理、更新方法、计算模式和特点,讨论了离散PSO的发展趋势和进一步研究方向。
The particle swarm optimization （PSO） algorithm is a new type global searching method based on swarm intelligence. The discrete forms and discretized methods have received more attention in recent years. The basic principles and mechanisms are introduced. Various improvements and applications of discrete PSO algorithms are reviewed. The mechanisms, updating methods, calculating mode and characteristics of two different discretized strategies are presented. Some future research directions about discrete PSO are proposed.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2008年第10期1986-1990,1994,共6页
Systems Engineering and Electronics
关键词
离散粒子群算法
组合优化问题
演化计算
群体智能
人工生命
discrete particle swarm optimization（DPSO）
combinatorial optimization problem
evolutionary computation
swarm intelligence
artificial life
