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FIFO Versus LIFO Issuing Policies for Stochastic Perishable Inventory Systems

Author

Listed:
  • Mahmut Parlar

    (McMaster University)

  • David Perry

    (University of Haifa)

  • Wolfgang Stadje

    (University of Osnabrück)

Abstract

We consider an inventory system for perishable items in which the arrival times of the items to be stored and the ones of the demands for those items form independent Poisson processes. The shelf lifetime of every item is finite and deterministic. Every demand is for a single item and is satisfied by one of the items on the shelf, if available. A demand remains unsatisfied if it arrives at an empty shelf. The aim of this paper is to compare two issuing policies: under FIFO (‘first in, first out’) any demand is satisfied by the item with the currently longest shelf life, while under LIFO (‘last in, first out’) always the youngest item on the shelf is assigned first. We determine the long-run net average profit as a function of the system parameters under each of the two policies, taking into account the revenue earned from satisfied demands, the cost of shelf space, penalties for unsatisfied demands, and the purchase cost of incoming items. The analytical results are used in several numerical examples in which the optimal input rate and the maximum expected long-run average profit under FIFO and under LIFO are determined and compared. We also provide a sensitivity analysis of the optimal solution for varying parameter values.

Suggested Citation

  • Mahmut Parlar & David Perry & Wolfgang Stadje, 2011. "FIFO Versus LIFO Issuing Policies for Stochastic Perishable Inventory Systems," Methodology and Computing in Applied Probability, Springer, vol. 13(2), pages 405-417, June.
    • Handle: RePEc:spr:metcap:v:13:y:2011:i:2:d:10.1007_s11009-009-9162-2
    DOI: 10.1007/s11009-009-9162-2
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    References listed on IDEAS

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    Cited by:

    1. Qing Li & Peiwen Yu & Xiaoli Wu, 2016. "Managing Perishable Inventories in Retailing: Replenishment, Clearance Sales, and Segregation," Operations Research, INFORMS, vol. 64(6), pages 1270-1284, December.
    2. Önal, Mehmet & Romeijn, H.Edwin & Sapra, Amar & van den Heuvel, Wilco, 2015. "The economic lot-sizing problem with perishable items and consumption order preference," European Journal of Operational Research, Elsevier, vol. 244(3), pages 881-891.
    3. Vahid Sarhangian & Hossein Abouee-Mehrizi & Opher Baron & Oded Berman, 2018. "Threshold-Based Allocation Policies for Inventory Management of Red Blood Cells," Manufacturing & Service Operations Management, INFORMS, vol. 20(2), pages 347-362, May.
    4. V. Yadavalli & Diatha Sundar & Swaminathan Udayabaskaran, 2015. "Two substitutable perishable product disaster inventory systems," Annals of Operations Research, Springer, vol. 233(1), pages 517-534, October.
    5. San-José, Luis A. & Sicilia, Joaquín & García-Laguna, Juan, 2014. "Optimal lot size for a production–inventory system with partial backlogging and mixture of dispatching policies," International Journal of Production Economics, Elsevier, vol. 155(C), pages 194-203.
    6. Babak Abbasi & Golnaz Vakili & Stuart Chesneau, 2017. "Impacts of Reducing the Shelf Life of Red Blood Cells: A View from Down Under," Interfaces, INFORMS, vol. 47(4), pages 336-351, August.

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