计算机应用与软件2017，Vol.34Issue(9)：302-305,4.DOI:10.3969/j.issn.1000-386x.2017.09.059
改进的多目标粒子群优化算法
AN IMPROVED MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION ALGORITHM
项铁铭 1王建成1
作者信息
- 1. 杭州电子科技大学天线与微波技术研究所 浙江杭州310018
- 折叠
摘要
Abstract
In order to improve the ability to solve the problem of multi-objective optimization (MOPSO),an improved multi-objective particle swarm optimization algorithm (IMOPSO) is proposed.Using IMSPSO,initial population was produced by a uniformly random initialization approach,and non-dominated solutions were selected by fast control strategy to generate the external archive.By comparing the successive generations of particles,we could judge whether they felled into local optima and adopted different updating strategies.At the same time,a disturbance item was added to the particle's updating.The experimental results show that the proposed algorithm significantly surpasses other algorithms in terms of GD(Generational Distance),SP(Spacing).关键词
外部档案/均匀初始化/快速支配策略/多目标粒子群优化算法/粒子信息档案Key words
External archive/Uniform and random initialization/Fast control strategy/MOPSO/Particle information archive分类
信息技术与安全科学引用本文复制引用
项铁铭,王建成..改进的多目标粒子群优化算法[J].计算机应用与软件,2017,34(9):302-305,4.
