基于微粒群算法的柔性流水车间调度优化  

PSO-based Optimization of Flexible Flow-shop Scheduling

作　　者：周辉仁[1] 唐万生[1] 魏颖辉[2] 

机构地区：[1]天津大学,天津300072 [2]辽宁科技学院,本溪117022

出　　处：《中国机械工程》2010年第9期1053-1057,共5页China Mechanical Engineering

基　　金：中国博士后科学基金资助项目(20090450759);辽宁省教育厅科研课题资助项目(20060439)

摘　　要：为了有效地解决柔性Flow-shop调度问题,提出用改进的微粒群算法进行求解,给出了一种能够保证个体合法性的编码方法;提出速度的计算公式采用自适应惯性权重和收缩因子相结合的方法。最后以某汽车发动机厂金加工车间的生产调度实例进行仿真,比较结果表明该算法的效果较好。In order to solve FFS problem efficiently,a new method solving FFS problem based on improved PSO algorithm was used.A new improved encoding method for the FFS problem could avoid illegal solution.The velocity formula adopting an adaptive inertia weight and constriction factor was proposed.Finally,an example of production scheduling problem for metalworking workshop in a car engine plant was simulated.Through comparison,the results show the effectiveness of the algorithm.

关 键 词：柔性Flow-shop调度 微粒群算法 编码方法 自适应惯性权重 

分 类 号：TP278[自动化与计算机技术—检测技术与自动化装置]