东南大学学报（英文版）2017，Vol.33Issue(4)：409-415,7.DOI:10.3969/j.issn.1003-7985.2017.04.004
改进粒子群算法集成解决动态单元构建与布局问题
Improved PSO for integrating dynamic cell formation and layout problems
摘要
Abstract
To decrease the impact of shorter product life cycles,dynamic cell formation problems (CFPs) and cell layout problems (CLPs) were simultaneously optimized.First,CFPs and CLPs were formally described.Due to the changes of product demands and the limit of machine capacity,the existing layout needed to be rearranged to a high degree.Secondly,a mathematical model was established for the objective function of minimizing the total costs.Thirdly,a novel dynamic multi-swarm particle swarm optimization (DMS-PSO) algorithm based on the communication learning strategy (CLS) was developed.To avoid falling into localoptimum and slow convergence,each swarm shared their optimal locations before regrouping.Finally,simulation experiments were conducted under different conditions.Numerical results indicate that the proposed algorithm has better stability and it converges faster than other existing algorithms.关键词
动态单元制造系统/单元构建与布局/沟通学习策略/动态多种群粒子群优化算法Key words
dynamic cellular manufacturing system/cell formation and layout/communication learning strategy/dynamic multi-swarm particle swarm optimization algorithm分类
机械制造引用本文复制引用
周炳海,陆裕斌..改进粒子群算法集成解决动态单元构建与布局问题[J].东南大学学报（英文版）,2017,33(4):409-415,7.基金项目
The National Natural Science Foundation of China (No.71471135). （No.71471135）
