IDEAS home Printed from https://ideas.repec.org/a/inm/ormsom/v15y2013i3p444-457.html
   My bibliography  Save this article

Supply Streams

Author

Listed:
  • Jing-Sheng Song

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • Paul Zipkin

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

Abstract

A supply stream is a continuous version of a supply chain. It is like a series inventory system, but stock can be held at any point along a continuum, not just at discrete stages. We assume stationary parameters and aim to minimize the long-run average total cost. We show that a stationary continuous-stage echelon base-stock policy is optimal. That is, at each geographic point along the supply stream, there is a target echelon inventory level, and the optimal policy at all times is to order and dispatch material so as to move the echelon inventory position as close as possible to this target. We establish this result by showing that the solutions to certain discrete-stage systems converge monotonically to a limit, as the distances between the stages become small, and this limit solves the continuous-stage system. With demand approximated by a Brownian motion, we show that, in the continuous-stage limit, the supply stream model is equivalent to one describing first-passage times. This linkage leads to some interesting and useful results. Specifically, we obtain a partial differential equation that characterizes the optimal cost function, and we find a closed-form expression for the optimal echelon base-stock levels in a certain special case, the first in the inventory literature. These expressions demonstrate that the well-known square-root law for safety stock does not apply in this context.

Suggested Citation

  • Jing-Sheng Song & Paul Zipkin, 2013. "Supply Streams," Manufacturing & Service Operations Management, INFORMS, vol. 15(3), pages 444-457, July.
  • Handle: RePEc:inm:ormsom:v:15:y:2013:i:3:p:444-457
    DOI: 10.1287/msom.2013.0431
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/msom.2013.0431
    Download Restriction: no

    File URL: https://libkey.io/10.1287/msom.2013.0431?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kevin H. Shang & Jing-Sheng Song, 2003. "Newsvendor Bounds and Heuristic for Optimal Policies in Serial Supply Chains," Management Science, INFORMS, vol. 49(5), pages 618-638, May.
    2. Fangruo Chen & Yu-Sheng Zheng, 1994. "Lower Bounds for Multi-Echelon Stochastic Inventory Systems," Management Science, INFORMS, vol. 40(11), pages 1426-1443, November.
    3. van Houtum, G. J. & Zijm, W. H. M., 1991. "Computational procedures for stochastic multi-echelon production systems," International Journal of Production Economics, Elsevier, vol. 23(1-3), pages 223-237, October.
    4. Andrew J. Clark & Herbert Scarf, 2004. "Optimal Policies for a Multi-Echelon Inventory Problem," Management Science, INFORMS, vol. 50(12_supple), pages 1782-1790, December.
    5. Awi Federgruen & Paul Zipkin, 1984. "Computational Issues in an Infinite-Horizon, Multiechelon Inventory Model," Operations Research, INFORMS, vol. 32(4), pages 818-836, August.
    6. Erica L. Plambeck & Amy R. Ward, 2006. "Optimal Control of a High-Volume Assemble-to-Order System," Mathematics of Operations Research, INFORMS, vol. 31(3), pages 453-477, August.
    7. Lingxiu Dong & Hau L. Lee, 2003. "Optimal Policies and Approximations for a Serial Multiechelon Inventory System with Time-Correlated Demand," Operations Research, INFORMS, vol. 51(6), pages 969-980, December.
    8. Gregory DeCroix & Jing-Sheng Song & Paul Zipkin, 2005. "A Series System with Returns: Stationary Analysis," Operations Research, INFORMS, vol. 53(2), pages 350-362, April.
    9. Sunil Kumar & Kumar Muthuraman, 2004. "A Numerical Method for Solving Singular Stochastic Control Problems," Operations Research, INFORMS, vol. 52(4), pages 563-582, August.
    10. Matthew J. Sobel, 2004. "Fill Rates of Single-Stage and Multistage Supply Systems," Manufacturing & Service Operations Management, INFORMS, vol. 6(1), pages 41-52, June.
    11. Guillermo Gallego & Paul Zipkin, 1999. "Stock Positioning and Performance Estimation in Serial Production-Transportation Systems," Manufacturing & Service Operations Management, INFORMS, vol. 1(1), pages 77-88.
    12. Martin I. Reiman & Rodrigo Rubio & Lawrence M. Wein, 1999. "Heavy Traffic Analysis of the Dynamic Stochastic Inventory-Routing Problem," Transportation Science, INFORMS, vol. 33(4), pages 361-380, November.
    13. Mark Broadie & Yusaku Yamamoto, 2003. "Application of the Fast Gauss Transform to Option Pricing," Management Science, INFORMS, vol. 49(8), pages 1071-1088, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. de Kok, Ton & Grob, Christopher & Laumanns, Marco & Minner, Stefan & Rambau, Jörg & Schade, Konrad, 2018. "A typology and literature review on stochastic multi-echelon inventory models," European Journal of Operational Research, Elsevier, vol. 269(3), pages 955-983.
    2. Diwakar Gupta & N. Selvaraju, 2006. "Performance Evaluation and Stock Allocation in Capacitated Serial Supply Systems," Manufacturing & Service Operations Management, INFORMS, vol. 8(2), pages 169-191, July.
    3. Woonghee Tim Huh & Ganesh Janakiraman & Mahesh Nagarajan, 2016. "Capacitated Multiechelon Inventory Systems: Policies and Bounds," Manufacturing & Service Operations Management, INFORMS, vol. 18(4), pages 570-584, October.
    4. Kevin H. Shang & Jing-Sheng Song, 2007. "Serial Supply Chains with Economies of Scale: Bounds and Approximations," Operations Research, INFORMS, vol. 55(5), pages 843-853, October.
    5. Li Chen & Jing-Sheng Song & Yue Zhang, 2017. "Serial Inventory Systems with Markov-Modulated Demand: Derivative Bounds, Asymptotic Analysis, and Insights," Operations Research, INFORMS, vol. 65(5), pages 1231-1249, October.
    6. Lingxiu Dong & Hau L. Lee, 2003. "Optimal Policies and Approximations for a Serial Multiechelon Inventory System with Time-Correlated Demand," Operations Research, INFORMS, vol. 51(6), pages 969-980, December.
    7. Retsef Levi & Robin Roundy & Van Anh Truong & Xinshang Wang, 2017. "Provably Near-Optimal Balancing Policies for Multi-Echelon Stochastic Inventory Control Models," Mathematics of Operations Research, INFORMS, vol. 42(1), pages 256-276, January.
    8. Noel Watson & Yu-Sheng Zheng, 2005. "Decentralized Serial Supply Chains Subject to Order Delays and Information Distortion: Exploiting Real-Time Sales Data," Manufacturing & Service Operations Management, INFORMS, vol. 7(2), pages 152-168, May.
    9. Gregory A. DeCroix, 2006. "Optimal Policy for a Multiechelon Inventory System with Remanufacturing," Operations Research, INFORMS, vol. 54(3), pages 532-543, June.
    10. Gregory A. DeCroix & Paul H. Zipkin, 2005. "Inventory Management for an Assembly System with Product or Component Returns," Management Science, INFORMS, vol. 51(8), pages 1250-1265, August.
    11. George Varlas & Michael Vidalis & Stelios Koukoumialos & Alexandros Diamantidis, 2021. "Optimal inventory control policies of a two-stage push–pull production inventory system with lost sales under stochastic production, transportation, and external demand," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 799-832, October.
    12. Peter Berling & Victor Martínez‐de‐Albéniz, 2016. "A characterization of optimal base‐stock levels for a multistage serial supply chain," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(1), pages 32-46, February.
    13. Geert-Jan van Houtum & Alan Scheller-Wolf & Jinxin Yi, 2007. "Optimal Control of Serial Inventory Systems with Fixed Replenishment Intervals," Operations Research, INFORMS, vol. 55(4), pages 674-687, August.
    14. Matthew J. Sobel & Volodymyr Babich, 2012. "Optimality of Myopic Policies for Dynamic Lot-Sizing Problems in Serial Production Lines with Random Yields and Autoregressive Demand," Operations Research, INFORMS, vol. 60(6), pages 1520-1536, December.
    15. Iida, Tetsuo, 2001. "The infinite horizon non-stationary stochastic multi-echelon inventory problem and near-myopic policies," European Journal of Operational Research, Elsevier, vol. 134(3), pages 525-539, November.
    16. Kevin H. Shang, 2012. "Single-Stage Approximations for Optimal Policies in Serial Inventory Systems with Nonstationary Demand," Manufacturing & Service Operations Management, INFORMS, vol. 14(3), pages 414-422, July.
    17. Ming Hu & Yi Yang, 2014. "Modified Echelon ( r, Q ) Policies with Guaranteed Performance Bounds for Stochastic Serial Inventory Systems," Operations Research, INFORMS, vol. 62(4), pages 812-828, August.
    18. Gregory DeCroix & Jing-Sheng Song & Paul Zipkin, 2005. "A Series System with Returns: Stationary Analysis," Operations Research, INFORMS, vol. 53(2), pages 350-362, April.
    19. Alp Muharremoglu & John N. Tsitsiklis, 2008. "A Single-Unit Decomposition Approach to Multiechelon Inventory Systems," Operations Research, INFORMS, vol. 56(5), pages 1089-1103, October.
    20. Mustafa Doğru & A. Kok & G. Houtum, 2013. "Newsvendor characterizations for one-warehouse multi-retailer inventory systems with discrete demand under the balance assumption," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(3), pages 541-559, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormsom:v:15:y:2013:i:3:p:444-457. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.