• DocumentCode
    3228970
  • Title

    Job-shop scheduling problem with multiple process routes considering lot split and setup time

  • Author

    Shaotan, Xu ; Yu, Huang ; Chaoyong, Zhang ; Kunlei, Lian

  • Author_Institution
    State Key Lab. of Digital Manuf. Equip. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2010
  • fDate
    23-26 Sept. 2010
  • Firstpage
    421
  • Lastpage
    425
  • Abstract
    To improve production efficiency and reduce makespan, this paper investigates lot scheduling with multiple process routes in job shop. Equal sublots are adopted and integrated with parallel translation model to optimize production cycle. Based on improved genetic algorithm (GA), a novel initialization method is used for chromosome encoding rationally. Then a new crossover operation is proposed for the problem. The computation results show that the improved genetic algorithm is feasible and effective.
  • Keywords
    genetic algorithms; job shop scheduling; crossover operation; equal sublots; improved genetic algorithm; job-shop scheduling problem; lot split; multiple process routes; parallel translation model; production cycle optimization; setup time; genetic algorithm; job shop; lot streaming;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-6437-1
  • Type

    conf

  • DOI
    10.1109/BICTA.2010.5645161
  • Filename
    5645161