摘要
微粒群算法是一种群体智能优化算法,它具有个体数目少、计算简单、鲁棒性好等优点;其缺点是容易陷入局部极值点,进化后期收敛速度慢且精度较差。本文对微粒群算法的基本原理、参数设置及优化进行了介绍,并对0-1背包问题的模型及目前的解决方法进行了简介。
Particle Swarm Optimization is an optimization algorithm based on swarm intelligence,the advantage of PSO is little individual amount,simply counting and good robustness, but PSO easily slump into best local extremum,and rapidity of convergence is slowly in the last stage of evolution. This paper introduced the fundamental principle, parameter settings and optimization of PSO. Model of 0-1 Knapsack Problem and solution are involved in this paper.
出处
《电脑知识与技术》
2007年第10期194-195,232,共3页
Computer Knowledge and Technology
关键词
微粒群算法
背包问题
参数设置
Particle Swarm Optimization
Knapsack Problems
parameter settings
