• DocumentCode
    2214782
  • Title

    Flexible job shop scheduling problems by a hybrid artificial bee colony algorithm

  • Author

    Li, Junqing ; Pan, Quanke ; Xie, Shengxian

  • Author_Institution
    Sch. of Comput., Liaocheng Univ., Liaocheng, China
  • fYear
    2011
  • fDate
    5-8 June 2011
  • Firstpage
    78
  • Lastpage
    83
  • Abstract
    In this paper, an effective artificial bee colony (ABC) algorithm is proposed for solving the flexible job shop scheduling problems. The total flow time criterion was considered. In the proposed algorithm, tabu search (TS) heuristic is introduced to perform local search for employed bee, onlookers, and scout bees. Meanwhile, an external Pareto archive set is employed to record enough non-dominated solutions for the problem considered. Experimental results on five well-known benchmarks show the efficiency of the proposed hybrid algorithm. It is concluded that the proposed algorithm is superior to the very recent algorithms in term of both search quality and computational efficiency.
  • Keywords
    Pareto optimisation; job shop scheduling; search problems; Pareto archive set; computational efficiency; flexible job shop scheduling problem; hybrid artificial bee colony algorithm flow time criterion; search quality; tabu search; Algorithm design and analysis; Computers; Job shop scheduling; Minimization; Optimization; Processor scheduling; artificial bee colony; flexible job shop scheduling problem; tabu search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2011 IEEE Congress on
  • Conference_Location
    New Orleans, LA
  • ISSN
    Pending
  • Print_ISBN
    978-1-4244-7834-7
  • Type

    conf

  • DOI
    10.1109/CEC.2011.5949601
  • Filename
    5949601