• DocumentCode
    3272640
  • Title

    Analyzing a stochastic inventory system for deteriorating items with stochastic lead time using simulation modeling

  • Author

    Alizadeh, Mohammadmahdi ; Eskandari, Hamidreza ; Sajadifar, S. Mehdi ; Geiger, Christopher D.

  • Author_Institution
    Sch. of Ind. Eng., Tarbiat Modares Univ., Tehran, Iran
  • fYear
    2011
  • fDate
    11-14 Dec. 2011
  • Firstpage
    1645
  • Lastpage
    1657
  • Abstract
    We consider an inventory system for continuous decaying items with stochastic lead time and Poisson demand. Shortage is allowed and all the unsatisfied demands are backlogged. Moreover, replenishment is one for one. Our objective is to minimize the long-run total expected cost of the system. Firstly, we have developed the mathematical model with deterministic lead time. Since the stochastic lead time makes the model complex especially when lead time has complicated probability distribution and it is difficult to prove convexity of the objective function, we have applied simulation modeling approach. The simulation model has no limitation on lead time or any other parameters. The simulation model is validated by comparing its outputs and analytical model´s results for the deterministic lead time case. Furthermore, we use optimizer module of the applied software to find near optimal solutions for a number of examples with stochastic lead time.
  • Keywords
    inventory management; statistical distributions; stochastic processes; Poisson demand; continuous decaying items; deteriorating items; deterministic lead time; mathematical model; objective function convexity; probability distribution; simulation modeling; stochastic inventory system; stochastic lead time; Analytical models; Educational institutions; Exponential distribution; Industrial engineering; Mathematical model; Software; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Simulation Conference (WSC), Proceedings of the 2011 Winter
  • Conference_Location
    Phoenix, AZ
  • ISSN
    0891-7736
  • Print_ISBN
    978-1-4577-2108-3
  • Electronic_ISBN
    0891-7736
  • Type

    conf

  • DOI
    10.1109/WSC.2011.6147881
  • Filename
    6147881