• DocumentCode
    3347319
  • Title

    Apply Inversion Order Number Genetic Algorithm to the Job Shop Scheduling Problem

  • Author

    Yang, Xiaomei ; Zeng, Jianchao ; Liang, Jiye

  • Author_Institution
    Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
  • fYear
    2009
  • fDate
    14-17 Oct. 2009
  • Firstpage
    196
  • Lastpage
    200
  • Abstract
    Through analyzing the present genetic operators to solve the job shop scheduling problem, a inversion order number genetic algorithm is proposed. In view of the quality of the inversion order number, this algorithm measures the population diversity by the relative inversion order number. It uses the information provided by the inversion order number of the individual and the offspring is generated. This algorithm not only satisfies the characteristic of the job shop scheduling problem, but also develops the search capacity of genetic algorithm. The computation results validate the effectiveness of the proposed algorithm.
  • Keywords
    genetic algorithms; job shop scheduling; genetic algorithm; inversion order number; job shop scheduling problem; Algorithm design and analysis; Biological system modeling; Computer integrated manufacturing; Educational institutions; Genetic algorithms; Intelligent systems; Job design; Job shop scheduling; Laboratories; Scheduling algorithm; Genetic Algorithm; inversion order number; the Job Shop Scheduling Problem;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genetic and Evolutionary Computing, 2009. WGEC '09. 3rd International Conference on
  • Conference_Location
    Guilin
  • Print_ISBN
    978-0-7695-3899-0
  • Type

    conf

  • DOI
    10.1109/WGEC.2009.104
  • Filename
    5402912