IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v48y2002i11p1486-1501.html
   My bibliography  Save this article

Optimal Stock Allocation for a Capacitated Supply System

Author

Listed:
  • Francis de Véricourt

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

  • Fikri Karaesmen

    (Department of Industrial Engineering, Koç University, 80910 Sariyer-Istanbul, Turkey)

  • Yves Dallery

    (Laboratoire Génie Industriel, Ecole Centrale Paris, Grande Voie des Vignes, 92295 Châtenay-Malabry Cedex, France)

Abstract

We consider a capacitated supply system that produces a single item that is demanded by several classes of customers. Each customer class may have a different backorder cost, so stock allocation arises as a key decision problem. We model the supply system as a multi customer make-to-stock queue. Using dynamic programming, we show that the optimal allocation policy has a simple and intuitive structure. In addition, we present an efficient algorithm to compute the parameters of this optimal allocation policy. Finally, for a typical supply chain design problem, we illustrate that ignoring the stock allocation dimension---a frequently encountered simplifying assumption---can lead to incorrect managerial decisions.

Suggested Citation

  • Francis de Véricourt & Fikri Karaesmen & Yves Dallery, 2002. "Optimal Stock Allocation for a Capacitated Supply System," Management Science, INFORMS, vol. 48(11), pages 1486-1501, November.
  • Handle: RePEc:inm:ormnsc:v:48:y:2002:i:11:p:1486-1501
    DOI: 10.1287/mnsc.48.11.1486.263
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.48.11.1486.263
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.48.11.1486.263?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. Morris A. Cohen & Paul R. Kleindorfer & Hau L. Lee, 1988. "Service Constrained (s, S) Inventory Systems with Priority Demand Classes and Lost Sales," Management Science, INFORMS, vol. 34(4), pages 482-499, April.
    2. Leroy B. Schwarz, 1989. "A Model for Assessing the Value of Warehouse Risk-Pooling: Risk-Pooling Over Outside-Supplier Leadtimes," Management Science, INFORMS, vol. 35(7), pages 828-842, July.
    3. Donald M. Topkis, 1968. "Optimal Ordering and Rationing Policies in a Nonstationary Dynamic Inventory Model with n Demand Classes," Management Science, INFORMS, vol. 15(3), pages 160-176, November.
    4. Steven Nahmias & W. Steven Demmy, 1981. "Operating Characteristics of an Inventory System with Rationing," Management Science, INFORMS, vol. 27(11), pages 1236-1245, November.
    5. Francis De Vericourt & Fikri Karaesmen & Yves Dallery, 2000. "Dynamic Scheduling in a Make-to-Stock System: A Partial Characterization of Optimal Policies," Operations Research, INFORMS, vol. 48(5), pages 811-819, October.
    6. Albert Y. Ha, 1997. "Inventory Rationing in a Make-to-Stock Production System with Several Demand Classes and Lost Sales," Management Science, INFORMS, vol. 43(8), pages 1093-1103, August.
    7. Gary D. Eppen, 1979. "Note--Effects of Centralization on Expected Costs in a Multi-Location Newsboy Problem," Management Science, INFORMS, vol. 25(5), pages 498-501, May.
    8. Francis de Véricourt & Fikri Karaesmen & Yves Dallery, 2001. "Assessing the Benefits of Different Stock-Allocation Policies for a Make-to-Stock Production System," Manufacturing & Service Operations Management, INFORMS, vol. 3(2), pages 105-121, December.
    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. Chen-Ritzo, Ching-Hua & Ervolina, Tom & Harrison, Terry P. & Gupta, Barun, 2011. "Component rationing for available-to-promise scheduling in configure-to-order systems," European Journal of Operational Research, Elsevier, vol. 211(1), pages 57-65, May.
    2. Teunter, Ruud H. & Klein Haneveld, Willem K., 2008. "Dynamic inventory rationing strategies for inventory systems with two demand classes, Poisson demand and backordering," European Journal of Operational Research, Elsevier, vol. 190(1), pages 156-178, October.
    3. Mohammad Najjartabar Bisheh & G. Reza Nasiri & Esmaeil Esmaeili & Hamid Davoudpour & Shing I. Chang, 2022. "A new supply chain distribution network design for two classes of customers using transfer recurrent neural network," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2604-2618, October.
    4. Felix Papier & Ulrich W. Thonemann, 2010. "Capacity Rationing in Stochastic Rental Systems with Advance Demand Information," Operations Research, INFORMS, vol. 58(2), pages 274-288, April.
    5. Saif Benjaafar & Mohsen ElHafsi & Tingliang Huang, 2010. "Optimal control of a production‐inventory system with both backorders and lost sales," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(3), pages 252-265, April.
    6. P. Escalona & F. Ordóñez & I. Kauak, 2017. "Critical level rationing in inventory systems with continuously distributed demand," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 273-301, January.
    7. Barut, M. & Sridharan, V, 2004. "Design and evaluation of a dynamic capacity apportionment procedure," European Journal of Operational Research, Elsevier, vol. 155(1), pages 112-133, May.
    8. Bing Lin & Shaoxiang Chen & Yi Feng & Jianjun Xu, 2018. "The Joint Stock and Capacity Rationings of a Make-To-Stock System with Flexible Demand," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(01), pages 1-27, February.
    9. ElHafsi, Mohsen & Camus, Herve & Craye, Etienne, 2010. "Managing an integrated production inventory system with information on the production and demand status and multiple non-unitary demand classes," European Journal of Operational Research, Elsevier, vol. 207(2), pages 986-1001, December.
    10. Ayanso, Anteneh & Diaby, Moustapha & Nair, Suresh K., 2006. "Inventory rationing via drop-shipping in Internet retailing: A sensitivity analysis," European Journal of Operational Research, Elsevier, vol. 171(1), pages 135-152, May.
    11. ElHafsi, Mohsen & Fang, Jianxin & Hamouda, Essia, 2021. "Optimal production and inventory control of multi-class mixed backorder and lost sales demand class models," European Journal of Operational Research, Elsevier, vol. 291(1), pages 147-161.
    12. Xu, Jianjun & Serrano, Alejandro & Lin, Bing, 2017. "Optimal production and rationing policy of two-stage tandem production system," International Journal of Production Economics, Elsevier, vol. 185(C), pages 100-112.
    13. Albert Y. Ha, 2000. "Stock Rationing in an M/E k /1 Make-to-Stock Queue," Management Science, INFORMS, vol. 46(1), pages 77-87, January.
    14. Alfieri, Arianna & Pastore, Erica & Zotteri, Giulio, 2017. "Dynamic inventory rationing: How to allocate stock according to managerial priorities. An empirical study," International Journal of Production Economics, Elsevier, vol. 189(C), pages 14-29.
    15. Elhafsi, Mohsen & Hamouda, Essia, 2018. "Managing an integrated production and inventory system selling to a dual market: Long-term and walk-in," European Journal of Operational Research, Elsevier, vol. 268(1), pages 215-230.
    16. Karin T. Möllering & Ulrich W. Thonemann, 2008. "An optimal critical level policy for inventory systems with two demand classes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 632-642, October.
    17. R. Dekker & R.M. Hill & M.J. Kleijn & R.H. Teunter, 2002. "On the (S − 1, S) lost sales inventory model with priority demand classes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(6), pages 593-610, September.
    18. Qing Ding & Panos Kouvelis & Joseph M. Milner, 2006. "Dynamic Pricing Through Discounts for Optimizing Multiple-Class Demand Fulfillment," Operations Research, INFORMS, vol. 54(1), pages 169-183, February.
    19. Liu, Shudong & Song, Miao & Tan, Kok Choon & Zhang, Changyong, 2015. "Multi-class dynamic inventory rationing with stochastic demands and backordering," European Journal of Operational Research, Elsevier, vol. 244(1), pages 153-163.
    20. Vinayak Deshpande & Morris A. Cohen & Karen Donohue, 2003. "A Threshold Inventory Rationing Policy for Service-Differentiated Demand Classes," Management Science, INFORMS, vol. 49(6), pages 683-703, June.

    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:ormnsc:v:48:y:2002:i:11:p:1486-1501. 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.