• DocumentCode
    2989911
  • Title

    A Modified Genetic Algorithm to Due Date of Job Shop Scheduling Problem

  • Author

    Zhu, Chuanjun ; Chen, Yurong ; Zhang, Chaoyong

  • Author_Institution
    Dept. of Mech. Eng., Hubei Automotive Ind. Inst., Shiyan, China
  • fYear
    2009
  • fDate
    18-20 Jan. 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper presents a modified genetic search algorithm for the non-regular job-shop scheduling problem with due date. The chromosome representation of the problem is based on the operation-based representation. In order to reduce the search space, the procedure for generating active schedules is constructed. For avoiding premature convergence in the conventional genetic algorithms (GA), the precedence operation crossover (POX) and approach of the generation alteration model are presented. The algorithm is tested on the instances for due date, the computation results validate the effectiveness of the proposed algorithm.
  • Keywords
    genetic algorithms; job shop scheduling; search problems; chromosome representation; conventional genetic algorithms; modified genetic search algorithm; nonregular job shop scheduling problem; operation-based representation; precedence operation crossover; Automotive engineering; Biological cells; Biological system modeling; Computational modeling; Encoding; Evolution (biology); Genetic algorithms; Job shop scheduling; Processor scheduling; Scheduling algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Network and Multimedia Technology, 2009. CNMT 2009. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-5272-9
  • Type

    conf

  • DOI
    10.1109/CNMT.2009.5374722
  • Filename
    5374722