基于微粒群算法的柔性流水车间调度优化被引量：18

PSO-based Optimization of Flexible Flow-shop Scheduling

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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.

作者周辉仁唐万生魏颖辉

机构地区天津大学辽宁科技学院

出处《中国机械工程》 EI CAS CSCD 北大核心 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)

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 flexible flow-shop scheduling（FFS） particle swarm optimization（PSO） encoding method adaptive inertia weight

分类号 TP278 [自动化与计算机技术—检测技术与自动化装置]

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