离散粒子群优化算法研究综述

Survey on discrete particle swarm optimization algorithm

粒子群优化(PSO)算法最初是基于连续空间的优化,然而现实世界中许多问题是离散的,近年来其离散化策略和方法受到广泛的关注.本文简要介绍PSO算法的工作原理和粒子更新机制、算法参数的分析与设置,详细介绍PSO算法的三种常见离散化策略的机理及其粒子更新机制,阐述离散PSO算法的应用成果,最后对其未来的研究方向进行展望.

Particle swarm optimization（PSO） algorithm is originally based on the continuous space optimization,but many of the problems in the real world are discrete.In recent years,its discrete strategies and methods arouse people＇s wide concern.This paper briefly describes the working principle and update mechanism of PSO,then analyses parameters＇ setting of the algorithm,we also describe the three common discrete PSO algorithms and their corresponding update mechanism in detail,and then present their application achievements.Finally,the prospects of the discrete PSO algorithm are given.