• DocumentCode
    1840966
  • Title

    An (s,S) inventory control model with return flows

  • Author

    Wang, Meijie ; Di, Weimin

  • Author_Institution
    Sch. of Environ. & Municipal Eng., North China Univ. of Water Resources & Electr. Power, Zhengzhou, China
  • Volume
    1
  • fYear
    2011
  • fDate
    13-15 May 2011
  • Firstpage
    328
  • Lastpage
    331
  • Abstract
    With the growth of environmental concerns, the reuse of used products has received increasing attention so that a new field “reverse logistics” has emerged. To improve inventory management performance of reverse logistics, an (s,S) inventory control model is presented comprising random demands and returns. For this model, an optimal control policy is derived, optimal control parameters are computed and the solving steps are described in detail. Moreover, probability distributions of net demands in two different situations, namely dependent and independent Poisson demands and returns, are calculated respectively, and applications of the model in these situations are carefully illustrated. Experimental study shows that the optimal parameters in independent situation are often smaller than that in dependent situation, so it is meaningful to analyze the relationships of item demands and returns in real-life practice in order to design a suitable inventory strategy.
  • Keywords
    Poisson distribution; environmental management; inventory management; optimal control; reverse logistics; stock control; (s,S) inventory control model; Poisson demands; Poisson returns; environmental growth; inventory management; optimal control policy; probability distributions; reverse logistics; Computational modeling; Inventory control; Mathematical model; Procurement; Random variables; Reverse logistics; inventory control policy; inventory management; reverse logistics; stochastic optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Business Management and Electronic Information (BMEI), 2011 International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-1-61284-108-3
  • Type

    conf

  • DOI
    10.1109/ICBMEI.2011.5916940
  • Filename
    5916940