求解多目标混流装配线平衡问题的VPS-PSO算法  

Multi-Objective Optimization of Mixed Assembly Line Balancing Problem Based on VPS-PSO Algorithm

作　　者：刘冬[1] 张卫[1] 陆宝春[1] LIU Dong;ZHANG Wei;LU Bao-chun(School of Mechanical Engineering Nanjing University of Science and Technology, Jiangsu Nanjing 210094, China)

机构地区：[1]南京理工大学机械工程学院,江苏南京210094

出　　处：《机械设计与制造》2019年第2期257-260,共4页Machinery Design & Manufacture

基　　金：江苏省产学研联合创新资金前瞻性研究项目(BY2015 004-09)

摘　　要：为了更有效地减少工作站数目、提高装配线效率,提出了一种基于多目标混流装配线平衡问题的方法。针对混流装配线平衡问题,采用工作站损失指数、装配线损失效率和平滑指数的评价指标作为混流装配线平衡优化问题的适应度函数,在给定节拍和装配优先顺序的前提下建立多目标优化模型。提出一种基于变种群策略的改进粒子群(VPS-PSO)算法能有效地维持种群的多样性,提高粒子群算法的全局搜索寻优能力。案例表明,该算法相对于PSO算法具有更好的寻优能力和求解效率,可以更高效地得到合理的装配线平衡方案。In order to decrease workstations and improve the efficiency, an approach of multi-objective mixed-model assembly line balancing problem was proposed. Aiming at the mixed-model assembly line balancing problem,the fitness function was taken by the loss index of workstation number,the loss efficiency of assembly lineand the smoothness index, and a multi-objective optimization model was established under the given tact and assembly priority order. Through the use of VPS-PSO(various population strategy-particle swarm optimization)algorithm can maintain the diversity of population particles and improve the performance of the algorithm’s global searching and optimization capabilities. The case indicated that the VPS-PSO algorithm can get a more rational assembly line balancing result which had a better search ability and solving efficiency compared withthe PSO algorithm.

关 键 词：混流装配线平衡问题 粒子群算法 变种群策略 多目标优化 

分 类 号：TH16[机械工程—机械制造及自动化]