• DocumentCode
    498886
  • Title

    A hybrid genetic algorithm for solving the economic lot scheduling problem (ELSP)

  • Author

    Qiu, Xuan ; Chang, Hui-you

  • Author_Institution
    Sch. of Software, Sun Yat-sen Univ., Guangzhou, China
  • Volume
    3
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    1315
  • Lastpage
    1320
  • Abstract
    In this paper, a hybrid genetic algorithm(HGA) is proposed to solve the ELSP. The ELSP is formulated using basic period(BP) approach. In the proposed HGA, the design of basic setups of GA is largely adopted from previous contributions. Four heuristic strategies are introduced in the proposed HGA, aiming at reaching feasible space easier, testing feasibility and avoiding falling into local optimum. To evaluate the performance of the proposed HGA, we apply it to Bomberger´s classical problem under 88% and 66% utilizations. Our experiments indicate that the proposed HGA outperforms traditional GA in getting minimum total cost and faster convergence rate. More importantly, our proposed HGA is showed to be capable of converging to global optimal solutions.
  • Keywords
    genetic algorithms; industrial economics; lot sizing; Bomberger classical problem; ELSP; HGA; basic period approach; economic lot scheduling problem; hybrid genetic algorithm; Costs; Cybernetics; Genetic algorithms; Job shop scheduling; Machine learning; Machine learning algorithms; Production; Scheduling algorithm; Software algorithms; Sun; Basic Period; Economic Lot Scheduling Problem; Genetic algorithm; Heuristics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2009 International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3702-3
  • Electronic_ISBN
    978-1-4244-3703-0
  • Type

    conf

  • DOI
    10.1109/ICMLC.2009.5212265
  • Filename
    5212265