微粒群优化算法及其改进形式综述

Summary of Particle Swarm Optimization and Its Improved Algorithms

微粒群优化算法是一类新的基于群体智能的启发式全局优化技术,群体中的每一个微粒代表待解决问题的一个候选解,算法利用微粒之间的相互作用发现复杂问题解空间的最优候选区域。该文综述了算法的基本形式及其多种改进形式,并给出了未来可能的研究方向。

Particle swarm optimization(PSO)is a new heuristic global optimization technique based on swarm intelli-gence.Each particle of the swarm represents one candidate solution of the problem being optimized.The algorithm finds optimal regions of complex problem spaces through the interaction of particles.This paper reviews the basic version and many kinds of improved versions of PSO,and future research issues are also given.