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An analysis of single item inventory systems with returns

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  • John A. Muckstadt
  • Michael H. Isaac

Abstract

Inventory systems with returns are systems in which there are units returned in a repairable state, as well as demands for units in a serviceable state, where the return and demand processes are independent. We begin by examining the control of a single item at a single location in which the stationary return rate is less than the stationary demand rate. This necessitates an occasional procurement of units from an outside source. We present a cost model of this system, which we assume is managed under a continuous review procurement policy, and develop a solution method for finding the policy parameter values. The key to the analysis is the use of a normally distributed random variable to approximate the steady‐state distribution of net inventory. Next, we study a single item, two echelon system in which a warehouse (the upper echelon) supports N(N ⩾ 1) retailers (the lower echelon). In this case, customers return units in a repairable state as well as demand units in a serviceable state at the retailer level only. We assume the constant system return rate is less than the constant system demand rate so that a procurement is required at certain times from an outside supplier. We develop a cost model of this two echelon system assuming that each location follows a continuous review procurement policy. We also present an algorithm for finding the policy parameter values at each location that is based on the method used to solve the single location problem.

Suggested Citation

  • John A. Muckstadt & Michael H. Isaac, 1981. "An analysis of single item inventory systems with returns," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 28(2), pages 237-254, June.
  • Handle: RePEc:wly:navlog:v:28:y:1981:i:2:p:237-254
    DOI: 10.1002/nav.3800280207
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    Cited by:

    1. Ki Ling Cheung & Alex X. Zhang, 1999. "The impact of inventory information distortion due to customer order cancellations," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(2), pages 213-231, March.
    2. Dong, Yachao & Maravelias, Christos T., 2021. "Terminal inventory level constraints for online production scheduling," European Journal of Operational Research, Elsevier, vol. 295(1), pages 102-117.
    3. Bimal Kumar Mawandiya & J. K. Jha & Jitesh J. Thakkar, 2020. "Optimal production-inventory policy for closed-loop supply chain with remanufacturing under random demand and return," Operational Research, Springer, vol. 20(3), pages 1623-1664, September.
    4. Le Thi Mai & Bui Loan Thuy, 2015. "Work-Family Role Conflict: A Survey of Woman Entrepreneurs in Hochiminh City," International Journal of Humanities, Arts and Social Sciences, Dr. Mohammad Hamad Al-khresheh, vol. 1(1), pages 36-47.
    5. Ashayeri, J. & Heuts, R.M.J. & Jansen, A. & Szczerba, B., 1994. "Inventory management of repairable service parts for personal computers : A case study," Other publications TiSEM 28578c62-2e4d-4345-929f-a, Tilburg University, School of Economics and Management.
    6. Hsien-Jen Lin, 2015. "Two-echelon stochastic inventory system with returns and partial backlogging," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(6), pages 966-975, April.
    7. Amy Cohn, 2006. "Composite-variable modeling for service parts logistics," Annals of Operations Research, Springer, vol. 144(1), pages 17-32, April.
    8. Gökbayrak, Esra & Kayış, Enis, 2023. "Single item periodic review inventory control with sales dependent stochastic return flows," International Journal of Production Economics, Elsevier, vol. 255(C).

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