• DocumentCode
    476016
  • Title

    Hybrid genetic-VNS algorithm with total flowtime minimization for the no-wait flowshop problem

  • Author

    Yang, Ning ; Li, Xiao-ping ; Zhu, Jie ; Wang, Qian

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Southeast Univ., Nanjing
  • Volume
    2
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    935
  • Lastpage
    940
  • Abstract
    In this paper, a hybrid genetic-VNS algorithm is proposed for the no-wait flowshop problem with total flowtime minimization. To avoid pitfalls of GA, such as poor local search capability and premature convergence, a rather effective VNS local search is introduced based on the framework of the improved GA. To fast convergence of the algorithm, ICH2 (an efficient composite heuristic) is used for the initial population generation. Experimental results show that the proposed algorithm outperforms other best two recent existing methods on both small and large instances.
  • Keywords
    flow shop scheduling; genetic algorithms; minimisation; composite heuristic; hybrid genetic-VNS algorithm; initial population generation; no-wait flowshop problem; scheduling problem; total flowtime minimization; Computer science; Convergence; Cybernetics; Genetic mutations; Job shop scheduling; Machine learning; Machine learning algorithms; Minimization methods; Stochastic processes; Thin film transistors; Hybrid Genetic-VNS algorithm; no-wait flowshop; scheduling; total flowtime;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4620539
  • Filename
    4620539