• DocumentCode
    2527754
  • Title

    An EOQ Model for Multi-Item and Multi-Storehouse Based on New Hybrid Genetic Algorithm

  • Author

    Zhao, Peixin ; Wang, Hong

  • Author_Institution
    Sch. of Manage., Shandong Univ., Jinan
  • Volume
    3
  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 1 2006
  • Firstpage
    657
  • Lastpage
    660
  • Abstract
    A new economic order quantity model is developed for multi-item and multi-storehouse with limited funds, limited storage capacity and stochastic demand. The model is proved to be a nonlinear convex programming. For finding the optimal replenishment schedule, we design a new hybrid genetic algorithm that combines self-adapting crossover and stochastic mutation operators. Comparing with the basic genetic algorithm, this improved algorithm adequately utilizes the adaptability information of current individuals, it has better convergence efficiency and higher solution precision. A numerical example is presented to illustrate the validity and efficiency of the new hybrid genetic algorithm
  • Keywords
    convex programming; genetic algorithms; industrial economics; inventory management; stochastic processes; economic order quantity model; genetic algorithm; multiitem multistorehouse model; nonlinear convex programming; optimal replenishment schedule; self-adapting crossover; stochastic demand; stochastic mutation operator; Capacity planning; Costs; Educational institutions; Finance; Financial management; Genetic algorithms; Genetic mutations; Industrial economics; Mathematical model; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    0-7695-2616-0
  • Type

    conf

  • DOI
    10.1109/ICICIC.2006.413
  • Filename
    1692262