• DocumentCode
    2144671
  • Title

    A Heuristic Algorithm for Large-Scale Job Shop Scheduling Based on Operation Decomposition Using Bottleneck Machine

  • Author

    Zhai, Yingni ; Sun, Shudong ; Wang, Junqiang ; Guo, Shihui

  • Author_Institution
    Key Lab. of Contemporary Design & Integrated Manuf. Technol., Northwestern Polytech. Univ., Xi´´an, China
  • fYear
    2010
  • fDate
    24-26 Aug. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A new heuristic algorithm for large-scale job shop scheduling problem is proposed based on operation decomposition using bottleneck machine. It detects bottleneck machine by orthogonal experiment. Based on the operations which are processed on the bottleneck machine, the large-scale job shop scheduling problem is divided into three sub-problems: the scheduling problem of the operations on bottleneck machine, pre-bottleneck machines and post-bottleneck machines. The operations on bottleneck machine are first scheduled by dispatching rules, and the other two sub-problems are solved by genetic algorithm to subordinate the schedule of the operations on bottleneck machine. A number of simulation results shown that the scheduling strategy and technique for the problem can improve the computing efficiency and quality of the solution.
  • Keywords
    design of experiments; genetic algorithms; heuristic programming; job shop scheduling; bottleneck machine; dispatching rules; genetic algorithm; heuristic algorithm; large-scale job shop scheduling strategy; operation decompositon; orthogonal experiment; Algorithm design and analysis; Dispatching; Equations; Job shop scheduling; Processor scheduling; Schedules;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management and Service Science (MASS), 2010 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5325-2
  • Electronic_ISBN
    978-1-4244-5326-9
  • Type

    conf

  • DOI
    10.1109/ICMSS.2010.5576038
  • Filename
    5576038