摘要
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 lim it 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.Toavoid falling into local optimum 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.
为了降低产品生命周期缩短对生产系统的影响,对动态单元构建与布局问题同时进行了优化.首先介绍了单元构建与布局问题,考虑到不同阶段的产品需求变化及机器产能限制,适当地将单元进行重新布置.然后,以最小化物料搬运费用为目标函数,建立了数学规划模型.其次,提出了基于沟通学习策略的动态多种群粒子群算法,使各种群粒子重组之前以规定策略进行位置共享,避免陷入局部最优和收敛较慢的困境.最后,在不同条件下进行了仿真对比实验,结果表明,所提出的算法具有更好的收敛稳定性以及更快的收敛速度.
基金
The National Natural Science Foundation of China(No.71471135)
