• DocumentCode
    532657
  • Title

    The improvement and optimization of Job Shop Scheduling Problem based on Genetic Algorithm

  • Author

    Zhengcheng, Wang ; Shuang, Zhou

  • Author_Institution
    Economic & Manage. Dept., ZheJiang Sci-Tech Univ., Hangzhou, China
  • Volume
    12
  • fYear
    2010
  • fDate
    22-24 Oct. 2010
  • Abstract
    This paper analyzes the mathematical model of Job Shop Scheduling Problem and improves traditional Genetic Algorithms by simplifying coding,optimizing crossover and mutation operator, and introduces selection operator with sifting strategy. The simulation results show that the global search ability is greatly better than that of traditional method. The improved Genetic Algorithms can solve Job Shop Scheduling Problem effectively.
  • Keywords
    genetic algorithms; job shop scheduling; genetic algorithm; job shop scheduling; optimization; Genetic Algorithm; Job Shop Scheduling Problem; Sifting Strategy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Application and System Modeling (ICCASM), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-7235-2
  • Electronic_ISBN
    978-1-4244-7237-6
  • Type

    conf

  • DOI
    10.1109/ICCASM.2010.5622133
  • Filename
    5622133