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混合粒子群算法在job-shop动态调度中的应用
引用本文:王策,王书锋,冯冬青,梁燕. 混合粒子群算法在job-shop动态调度中的应用[J]. 计算机工程与应用, 2010, 46(26): 219-222. DOI: 10.3778/j.issn.1002-8331.2010.26.068
作者姓名:王策  王书锋  冯冬青  梁燕
作者单位:郑州大学 电气工程学院,郑州 450001
摘    要:提出了基于事件驱动的动态调度策略,以融合遗传算法的粒子群算法来实现作业车间生产调度,有很好的收敛精度;在此基础上,对作业车间生产调度中的工件增加及取消、机器故障等各种动态事件进行了研究,能在扰动后提供新的调度计划,有效地解决了车间动态调度的一致性和连续性的问题。

关 键 词:作业车间生产调度  粒子群算法  遗传算法  动态事件  
收稿时间:2009-02-23
修稿时间:2009-4-9 

Application of hybrid PSO in job-shop dynamic scheduling problem
WANG Ce,WANG Shu-feng,FENG Dong-qing,LIANG Yan. Application of hybrid PSO in job-shop dynamic scheduling problem[J]. Computer Engineering and Applications, 2010, 46(26): 219-222. DOI: 10.3778/j.issn.1002-8331.2010.26.068
Authors:WANG Ce  WANG Shu-feng  FENG Dong-qing  LIANG Yan
Affiliation:Department of Electrical Engineering,Zhengzhou University,Zhengzhou 450001,China
Abstract:A new event-driven strategy of dynamic scheduling has been introduced in this paper.The particle swarm optimization which combining a genetic algorithm is used in the job shop scheduling, which has a good astringency.The dynamic events which concerning machine,job and examination have been researched in this paper and a new plan can be provided by part-renovating ,which can solve the problem of consistency and continuity in dynamic scheduling.
Keywords:job shop scheduling problem  particle swarm optimization  genetic algorithm  dynamic events
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