计算机工程2011，Vol.37Issue(14)：152-154,3.DOI:10.3969/j.issn.1000-3428.2011.14.050
基于均匀设计的聚类多目标粒子群优化算法
Clustering Multi-objective Particle Swarm Optimization Algorithm Based on Uniform Design
摘要
Abstract
In order to solve multi-objective problems efficiently, this paper proposes a clustering multi-objective Particle Swarm Optimization (PSO) algorithm based on uniform design named UCMOPSO. Crossover operation based on uniform design is adjusted to get uniformly distributed solutions in objective space to help swarm to escape from local optima, and a new clustering operator is introduced to select the representative non-dominated solutions, which decreases the computation complexity and limits the size of the external archive. Experimental results based on benchmark functions indicate that UCMOPSO has superiority in convergence and distribution compared with other algorithms.关键词
均匀设计/多目标优化/聚类/粒子群优化算法/外部存档Key words
uniform design/ multi-objective optimization/ clustering/ Particle Swarm Optimization(PSO) algorithm/ external archive分类
信息技术与安全科学引用本文复制引用
刘衍民,牛奔,赵庆祯..基于均匀设计的聚类多目标粒子群优化算法[J].计算机工程,2011,37(14):152-154,3.基金项目
广东省自然科学基金资助项目(9451806001002294) （9451806001002294）
贵州省教育厅社科基金资助项目(0705204) （0705204）
山东省科技攻关计划基金资助项目(2009GG10001008) （2009GG10001008）
