• DocumentCode
    238799
  • Title

    A memetic algorithm for solving flexible Job-Shop Scheduling Problems

  • Author

    Wenping Ma ; Yi Zuo ; Jiulin Zeng ; Shuang Liang ; Licheng Jiao

  • Author_Institution
    Key Lab. of Intell. Perception & Image Understanding of Minist. of Educ. of China, Xidian Univ., Xi´an, China
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    66
  • Lastpage
    73
  • Abstract
    The flexible Job-shop Scheduling Problem (FJSP) is an extension of the classical job-shop scheduling problem (JSP). In this paper, a memetic algorithm (MA) for the FJSP is presented. This MA is a hybrid genetic algorithm which explores the search space and two efficient local searchers to exploit information in the search region. An extensive computational study on 49 benchmark problems shows that the algorithm is effective and robust, with respect to other well-known effective algorithms.
  • Keywords
    genetic algorithms; job shop scheduling; search problems; FJSP; MA; classical job-shop scheduling problem; flexible job-shop scheduling problems; hybrid genetic algorithm; local searchers; memetic algorithm; search space; Evolutionary computation; flexible job-shop scheduling; memetic algorithm; simulated annealing; tabu search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2014 IEEE Congress on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-6626-4
  • Type

    conf

  • DOI
    10.1109/CEC.2014.6900332
  • Filename
    6900332
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=238799