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采用实时生产信息的单元制造任务动态调度方法 被引量:5

Dynamic Job Scheduling Method with Real-Time Production Information for Manufacturing Cell
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摘要 运用无线射频技术来实现对制造单元加工现场实时生产信息的动态获取,并针对制造单元生产过程中常发生的新任务加入、设备损坏和交货期更改的不确定性事件,以制造任务最短完工时间为调度目标,建立了单元制造任务的动态调度模型,通过引入爬山搜索方法构建了混合遗传算法,实现了对该模型的有效解算.混合遗传算法的进化操作由选择、交叉、变异与爬山进化算子组成,可有效地提高算法的收敛速度,在开发的采用实时生产信息的单元制造任务动态调度系统上进行了调度案例验证,结果表明,所提出的方法可以有效地解决不确定性事件的单元制造任务的动态调度问题,从而提高了调度方案与制造单元实际生产需求的一致性. A dynamic job scheduling method is proposed, where radio frequency identification technology is adopted to collect the real-time production information related to workpieces, operations and facilities produced at the manufacturing spots; on the basis, to deal with the three types of uncertain events including new jobs arrival, facility breakdown and delivery-time change occurred in the manufacturing cell production, taking the shortest finishing time of jobs as the scheduling objective, a dynamic job scheduling mathematical model is established and solved with hybrid genetic algorithm designed by introducing hill-climbing searching method. Four evolution operators consisting of selection, crossover, mutation and hill-climbing are designed to effectively improve the convergence speed of the algorithm. A prototype system of dynamic job scheduling based on real-time production information is developed. The job scheduling case study is carried out and the results show that the proposed job scheduling method enables to deal with the dynamic job scheduling problems for uncertain events efficiently to improve the consistency between scheduling solutions and practical requirements of manufacturing cell production.
出处 《西安交通大学学报》 EI CAS CSCD 北大核心 2009年第11期56-60,共5页 Journal of Xi'an Jiaotong University
基金 国家自然科学基金资助项目(50605050 50805116) 西安交通大学机械制造系统工程国家重点实验室开发基金资助项目
关键词 任务调度 无线射频 不确定性事件 混合遗传算法 job scheduling radio frequency identification uncertain events hybrid genetic algorithm
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参考文献10

  • 1SAKAWA M, MORI T. An efficient genetic algorithm for job-shop scheduling problems with fuzzy processing time and fuzzy due date [J]. Computers and Industrial Engineering, 1999, 36(2): 325-341.
  • 2MATTFELD D C, BIERWIRTH C. An efficient genetic algorithm for job shop scheduling with tardiness objectives [J]. European Journal of Operational Research,2004, 155(3): 616-630.
  • 3YUN Y So Genetic algorithm with fuzzy logic controller for preemptive and non-preemptive job-shop scheduling problems [J]. Computers and Industry Engineering, 2002, 43(3): 623-644.
  • 4VINOD V, SRIDHARAN R. Scheduling a dynamic job shop production system with sequence-dependent setups: an experimental study [J]. Robotics and Computer-Integrated Manufacturing, 2008(24): 435-449.
  • 5周光辉,江平宇,黄国全.客户竞争驱动的任务调度非合作博弈[J].机械工程学报,2006,42(7):56-61. 被引量:4
  • 6WEINSTEIN R. RFID.. a technical overview and its application to the enterprise [J]. IT Professional, 2005, 7(3): 23-27.
  • 7CHOWHKH, CHOYKL, LEEWB. Design of a RFID case-based resource management system for warehouse operations [J]. Expert Systems with Appli cations, 2006, 30(4): 561-576.
  • 8CHOW H K H, CHOY K L, LEE W B. Adynamic logistics process knowledge-based system-an RFID multi agent approach [J]. Knowledge-Based Systems, 2007, 20(4): 357-372.
  • 9ZHOU Guanghui, JIANG Pingyu,HUANG Guoquan. A game-theory approach for job scheduling in networked manufacturing[J]. International Journal of Advanced Manufacturing Technology, 2009, 41 (9/ 10) : 972-985.
  • 10ALI R Y. An effective hybrid immune-hill climbing optimization approach for solving design and manufacturing optimization problems in industry [J]. Journal of Materials Processing Technology, 2009, 209 (6):2773-2780.

二级参考文献7

  • 1MATTFELD D C,BIERWIRTH C.An efficient genetic algorithm for job shop scheduling with tardiness objectives[J].European Journal of Operational Research,2004,155:616-630.
  • 2LI Guofu,YE Feifan.Scheduling flow shops in the environment of multi-functional machine tools[J].Computers & Industry Engineering,2002,42:163-168.
  • 3KIM Y K,PARK K,KO J.A symbiotic evolutionary algorithm for the integration of process planning and job shop scheduling[J].Computers & Operations Research,2003,30:1 151-1 171.
  • 4SON Y S,BALDICK R.Hybrid coevolutionary programming for Nash equilibrium search in games with local optima[J].IEEE Transactions on Evolutionary Computation,2004,8(4):305 -315.
  • 5廖强,周凯.用遗传算法解决作业车间的调度优化问题[J].计算机集成制造系统-CIMS,1999,5(5):62-64. 被引量:5
  • 6潘全科,孙志峻,朱剑英.基于遗传算法的作业车间调度优化[J].信息与控制,2002,31(3):216-218. 被引量:12
  • 7李正龙.一种n人静态博弈纯策略纳什均衡存在性判别法[J].运筹与管理,2004,13(1):33-37. 被引量:7

共引文献3

同被引文献36

  • 1张晓建.切削技术与刀具管理的现状与发展趋势[J].装备维修技术,2005(2):8-13. 被引量:6
  • 2吴宁,王建华,李富平,谢川.数控加工中刀具射频识别技术的实现[J].组合机床与自动化加工技术,2005(5):73-74. 被引量:7
  • 3JIANG Pingyu,ZHOU Guanghui,ZHAO Gang,et al.E-2-MES:an e-service-driven networked manufacturing platform for extended enterprises[J].International Journal of Computer Integrated Manufacturing,2007,20(2/3):127-142.
  • 4ZHOU Guanghui,JIANG Pingyu,ZHANG Guohai.Game theoretical framework for process plan decision of jobs in networked manufacturing[C]//Proceedings of the IEEE International Conference on Automation and Logistics.Piscataway,NJ USA:IEEE,2007:1868-1873.
  • 5SAKAWA M,MORI T.An efficient genetic algorithm for job-shop scheduling problems with fuzzy processing time and fuzzy due date[J].Computers & Industrial Engineering,1999,36(2):325-341.
  • 6MATTFELD D C,BIERWIRTH C.An efficient genetic algorithm for job shop scheduling with tardiness objectives[J].European Journal of Operational Research,2004,155(3):616-630.
  • 7YUN Y S.Genetic algorithm with fuzzy logic controller for preemptive and non-preemptive joh-shop scheduling problems[J].Computers & Industry Engineering,2002,43(3):623-644.
  • 8KIM B H.A new game-theoretic framework for maintenance strategy analysis[J].IEEE Transactions on Powet Systems,2003,18(2):698-706.
  • 9ALI R Y.An effective hybrid immune-hill climbing optimization approach for solving design and manufacturing optimization problems in industry[J].Journal of Materials Processing Technology,2009,209(6):Z773-2780.
  • 10SRINIVAS M,PATNAIK L M.Adaptive probabilities of crossover and mutation in genetic algorithm[J].IEEE Tram on Systems,Man and Cybernetics,1994,24(4):656-667.

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