• DocumentCode
    176638
  • Title

    An inventory control model for perishable items with stochastic replenishment interval and stock-dependent selling rate

  • Author

    Guang-fan Xu ; Xiao-jia Wang ; Yan-yan Wu ; Shan-Lin Yang

  • Author_Institution
    Sch. of Manage., Hefei Univ. of Technol., Hefei, China
  • fYear
    2014
  • fDate
    May 31 2014-June 2 2014
  • Firstpage
    3573
  • Lastpage
    3579
  • Abstract
    Periodic replenishment inventory models are widely used in practice, especially for inventory systems in which many different goods are purchased from the same supplier. However, most of periodic replenishment inventory models have assumed a fixed length of the replenishment periods. In practice, it is possible that the replenishment periods are of a stochastic length. This paper presents an inventory control model for deteriorating items in the case of random replenishment intervals and stock-dependent selling rate. The replenishment interval is assumed to obey from two different distributions, namely, exponential and uniform distributions. Also, shortages are allowed in the term of partial backordering. For this model, we provide the necessary and sufficient conditions of the existence and uniqueness of the optimal solutions and a procedure is also developed to determine the optimal solution for the proposed models. At last, numerical example is shown to illuminate the presented model.
  • Keywords
    exponential distribution; stochastic processes; stock control; deteriorating items; exponential distributions; inventory control model; necessary and sufficient conditions; partial backordering; periodic replenishment inventory models; perishable items; random replenishment intervals; stochastic replenishment interval; stock-dependent selling rate; uniform distributions; Art; Production; deteriorating items; inventory control; partial backlogging; stochastic replenishment interval; stock-dependent selling rate;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (2014 CCDC), The 26th Chinese
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4799-3707-3
  • Type

    conf

  • DOI
    10.1109/CCDC.2014.6852799
  • Filename
    6852799