• DocumentCode
    3758795
  • Title

    Job shop scheduling based on genetic algorithm using Matlab

  • Author

    Xiao Yang;Jianming Wang;Minglei Hou;Xiaoliang Fan

  • Author_Institution
    School of Energy Power and Mechanical Engineering, North China Electric Power University, Baoding, China
  • fYear
    2015
  • Firstpage
    772
  • Lastpage
    775
  • Abstract
    This paper briefly introduces the principle and characteristics of genetic algorithm, as well as the basic operation and the solving steps. The fitness function was built based on the objective function. The operator algorithms of replication, crossover and mutation were designed. The flexible job shop scheduling is optimized by designing the program based on MATLAB using the genetic algorithm. The genetic algorithm in this paper is tested on instances taken from the literature and compared with their results. The computation results show that the genetic algorithm referred in this paper is feasible and effective.
  • Keywords
    "Decision support systems","Job shop scheduling","MATLAB","Genetic algorithms","Erbium","Sociology","Statistics"
  • Publisher
    ieee
  • Conference_Titel
    Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2015 IEEE
  • Print_ISBN
    978-1-4799-1979-6
  • Type

    conf

  • DOI
    10.1109/IAEAC.2015.7428660
  • Filename
    7428660