Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (26): 219-222.DOI: 10.3778/j.issn.1002-8331.2010.26.068

• 工程与应用 • Previous Articles     Next Articles

Application of hybrid PSO in job-shop dynamic scheduling problem

WANG Ce,WANG Shu-feng,FENG Dong-qing,LIANG Yan   

  1. Department of Electrical Engineering,Zhengzhou University,Zhengzhou 450001,China
  • Received:2009-02-23 Revised:2009-04-09 Online:2010-09-11 Published:2010-09-11
  • Contact: WANG Ce

混合粒子群算法在job-shop动态调度中的应用

王 策,王书锋,冯冬青,梁 燕   

  1. 郑州大学 电气工程学院,郑州 450001
  • 通讯作者: 王 策

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.

Key words: job shop scheduling problem, particle swarm optimization, genetic algorithm, dynamic events

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

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