IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v50y2004i10p1431-1448.html
   My bibliography  Save this article

Demand Allocation in Multiple-Product, Multiple-Facility, Make-to-Stock Systems

Author

Listed:
  • Saif Benjaafar

    (Graduate Program in Industrial Engineering, Department of Mechanical Engineering, University of Minnesota, Minneapolis, Minnesota 55455-0111)

  • Mohsen ElHafsi

    (The A. Gary Anderson Graduate School of Management, University of California, Riverside, California 92521-0203)

  • Francis de Véricourt

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

Abstract

We consider the problem of allocating demand arising from multiple products to multiple production facilities with finite capacity and load-dependent lead times. Production facilities can choose to manufacture items either to stock or to order. Products vary in their demand rates, holding and backordering costs, and service-level requirements. We develop models and solution procedures to determine the optimal allocation of demand to facilities and the optimal inventory level for products at each facility. We consider two types of demand allocation, one in which we allow the demand for a product to be split among multiple facilities and the other in which demand from each product must be entirely satisfied by a single facility. We also consider two forms of inventory warehousing, one in which inventory locations are factory based and one in which they are centralized. For each case, we offer a solution procedure to obtain optimal demand allocations and optimal inventory base-stock levels. For systems with multiple customer classes, we also determine optimal inventory rationing levels for each class for each product. We use the models to characterize analytically several properties of the optimal solution. In particular, we highlight eight principles that relate the effects of cost, congestion, inventory pooling, multiple sourcing, customer segmentation, inventory rationing, and process and demand variability.

Suggested Citation

  • Saif Benjaafar & Mohsen ElHafsi & Francis de Véricourt, 2004. "Demand Allocation in Multiple-Product, Multiple-Facility, Make-to-Stock Systems," Management Science, INFORMS, vol. 50(10), pages 1431-1448, October.
  • Handle: RePEc:inm:ormnsc:v:50:y:2004:i:10:p:1431-1448
    DOI: 10.1287/mnsc.1040.0250
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.1040.0250
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mnsc.1040.0250?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. Linda V. Green & Debashis Guha, 1995. "Note: On the Efficiency of Imbalance in Multi-Facility Multi-Server Service Systems," Management Science, INFORMS, vol. 41(1), pages 179-187, January.
    2. Marshall L. Fisher, 1981. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 27(1), pages 1-18, January.
    3. 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.
    4. Zhen Liu & Rhonda Righter, 1998. "Optimal Load Balancing on Distributed Homogeneous Unreliable Processors," Operations Research, INFORMS, vol. 46(4), pages 563-573, August.
    5. Saif Benjaafar & William L. Cooper & Joon-Seok Kim, 2005. "On the Benefits of Pooling in Production-Inventory Systems," Management Science, INFORMS, vol. 51(4), pages 548-565, April.
    6. Yu-Sheng Zheng & Paul Zipkin, 1990. "A Queueing Model to Analyze the Value of Centralized Inventory Information," Operations Research, INFORMS, vol. 38(2), pages 296-307, April.
    7. Albert Y. Ha, 1997. "Optimal Dynamic Scheduling Policy for a Make-To-Stock Production System," Operations Research, INFORMS, vol. 45(1), pages 42-53, February.
    8. Lawrence M. Wein, 1992. "Dynamic Scheduling of a Multiclass Make-to-Stock Queue," Operations Research, INFORMS, vol. 40(4), pages 724-735, August.
    9. Paul H. Zipkin, 1995. "Performance Analysis of a Multi-Item Production-Inventory System Under Alternative Policies," Management Science, INFORMS, vol. 41(4), pages 690-703, April.
    10. Cattrysse, Dirk G. & Van Wassenhove, Luk N., 1992. "A survey of algorithms for the generalized assignment problem," European Journal of Operational Research, Elsevier, vol. 60(3), pages 260-272, August.
    11. 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.
    12. Tang, Christopher S. & van Vliet, Mario, 1994. "Traffic allocation for manufacturing systems," European Journal of Operational Research, Elsevier, vol. 75(1), pages 171-185, May.
    13. William P. Peterson, 1991. "A Heavy Traffic Limit Theorem for Networks of Queues with Multiple Customer Types," Mathematics of Operations Research, INFORMS, vol. 16(1), pages 90-118, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jean-Philippe Gayon & Saif Benjaafar & Francis de Véricourt, 2009. "Using Imperfect Advance Demand Information in Production-Inventory Systems with Multiple Customer Classes," Manufacturing & Service Operations Management, INFORMS, vol. 11(1), pages 128-143, July.
    2. Ibtissem Ernez-Gahbiche & Khaled Hadjyoussef & Abdelwaheb Dogui & Zied Jemai, 2019. "Decentralized versus cooperative performances in a Nash game between a customer and two suppliers," Flexible Services and Manufacturing Journal, Springer, vol. 31(2), pages 279-307, June.
    3. Abhilasha Prakash Katariya & Sıla Çetinkaya & Eylem Tekin, 2014. "Cyclic Consumption and Replenishment Decisions for Vendor-Managed Inventory of Multisourced Parts in Dell’s Supply Chain," Interfaces, INFORMS, vol. 44(3), pages 300-316, June.
    4. Van Nieuwenhuyse, Inneke & Vandaele, Nico & Rajaram, Kumar & Karmarkar, Uday S., 2007. "Buffer sizing in multi-product multi-reactor batch processes: Impact of allocation and campaign sizing policies," European Journal of Operational Research, Elsevier, vol. 179(2), pages 424-443, June.
    5. Feng, Jiejian & Zhang, Michael, 2017. "Dynamic quotation of leadtime and price for a Make-To-Order system with multiple customer classes and perfect information on customer preferences," European Journal of Operational Research, Elsevier, vol. 258(1), pages 334-342.
    6. Saif Benjaafar & William L. Cooper & Joon-Seok Kim, 2005. "On the Benefits of Pooling in Production-Inventory Systems," Management Science, INFORMS, vol. 51(4), pages 548-565, April.
    7. Sanajian, Nima & BalcIog[small tilde]lu, BarIs, 2009. "The impact of production time variability on make-to-stock queue performance," European Journal of Operational Research, Elsevier, vol. 194(3), pages 847-855, May.
    8. Saif Benjaafar & Mohsen ElHafsi, 2006. "Production and Inventory Control of a Single Product Assemble-to-Order System with Multiple Customer Classes," Management Science, INFORMS, vol. 52(12), pages 1896-1912, December.
    9. ElHafsi, Mohsen, 2009. "Optimal integrated production and inventory control of an assemble-to-order system with multiple non-unitary demand classes," European Journal of Operational Research, Elsevier, vol. 194(1), pages 127-142, April.
    10. Hui Zhao & Jennifer K. Ryan & Vinayak Deshpande, 2008. "Optimal Dynamic Production and Inventory Transshipment Policies for a Two-Location Make-to-Stock System," Operations Research, INFORMS, vol. 56(2), pages 400-410, April.
    11. Ali, Agha Iqbal & O'Connor, Debra J., 2010. "The impact of distribution system characteristics on computational tractability," European Journal of Operational Research, Elsevier, vol. 200(2), pages 323-333, January.
    12. Saif Benjaafar & Yanzhi Li & Dongsheng Xu & Samir Elhedhli, 2008. "Demand Allocation in Systems with Multiple Inventory Locations and Multiple Demand Sources," Manufacturing & Service Operations Management, INFORMS, vol. 10(1), pages 43-60, October.
    13. Ashesh Kumar Sinha & Ananth Krishnamurthy, 2020. "Production and Capacity Utilization Strategies in Supply Chains for Complex Engineered Products," Production and Operations Management, Production and Operations Management Society, vol. 29(2), pages 462-480, February.
    14. Yang Yu & Ray Qing Cao & Dara Schniederjans, 2017. "Cloud computing and its impact on service level: a multi-agent simulation model," International Journal of Production Research, Taylor & Francis Journals, vol. 55(15), pages 4341-4353, August.
    15. Shuang Chen & Joseph Geunes, 2013. "Optimal allocation of stock levels and stochastic customer demands to a capacitated resource," Annals of Operations Research, Springer, vol. 203(1), pages 33-54, March.
    16. Josh Reed & Bo Zhang, 2017. "Managing capacity and inventory jointly for multi-server make-to-stock queues," Queueing Systems: Theory and Applications, Springer, vol. 86(1), pages 61-94, June.
    17. Saif Benjaafar & Ehsan Elahi & Karen L. Donohue, 2007. "Outsourcing via Service Competition," Management Science, INFORMS, vol. 53(2), pages 241-259, February.
    18. Richard Pibernik & Prashant Yadav, 2008. "Dynamic capacity reservation and due date quoting in a make‐to‐order system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 55(7), pages 593-611, October.
    19. Hossein Abouee‐Mehrizi & Oded Berman & Hassan Shavandi & Ata G. Zare, 2011. "An exact analysis of a joint production‐inventory problem in two‐echelon inventory systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(8), pages 713-730, December.
    20. Jing-Sheng Song & Yue Zhang, 2020. "Stock or Print? Impact of 3-D Printing on Spare Parts Logistics," Management Science, INFORMS, vol. 66(9), pages 3860-3878, September.
    21. Vladimir Kovtun & Avi Giloni & Clifford Hurvich & Sridhar Seshadri, 2023. "Pivot Clustering to Minimize Error in Forecasting Aggregated Demand Streams Each Following an Autoregressive Moving Average Model," Stats, MDPI, vol. 6(4), pages 1-28, November.

    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. Saif Benjaafar & Yanzhi Li & Dongsheng Xu & Samir Elhedhli, 2008. "Demand Allocation in Systems with Multiple Inventory Locations and Multiple Demand Sources," Manufacturing & Service Operations Management, INFORMS, vol. 10(1), pages 43-60, October.
    2. Bora Kat & Zeynep Avṣar, 2011. "Using aggregate fill rate for dynamic scheduling of multi-class systems," Annals of Operations Research, Springer, vol. 182(1), pages 87-117, January.
    3. William Liang & Barış Balcıog̃lu & Robert Svaluto, 2013. "Scheduling policies for a repair shop problem," Annals of Operations Research, Springer, vol. 211(1), pages 273-288, December.
    4. H. G. H. Tiemessen & M. Fleischmann & G. J. Houtum, 2017. "Dynamic control in multi-item production/inventory systems," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 165-191, January.
    5. Saif Benjaafar & William L. Cooper & Joon-Seok Kim, 2005. "On the Benefits of Pooling in Production-Inventory Systems," Management Science, INFORMS, vol. 51(4), pages 548-565, April.
    6. N Sanajian & H Abouee-Mehrizi & B Balcıog̃lu, 2010. "Scheduling policies in the M/G/1 make-to-stock queue," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 115-123, January.
    7. Ioannis Ch. Paschalidis & Yong Liu, 2003. "Large Deviations-Based Asymptotics for Inventory Control in Supply Chains," Operations Research, INFORMS, vol. 51(3), pages 437-460, June.
    8. 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.
    9. Hossein Abouee-Mehrizi & Opher Baron & Oded Berman, 2014. "Exact Analysis of Capacitated Two-Echelon Inventory Systems with Priorities," Manufacturing & Service Operations Management, INFORMS, vol. 16(4), pages 561-577, October.
    10. Chen Shaoxiang, 2004. "The Optimality of Hedging Point Policies for Stochastic Two-Product Flexible Manufacturing Systems," Operations Research, INFORMS, vol. 52(2), pages 312-322, April.
    11. Ganesh Janakiraman & Mahesh Nagarajan & Senthil Veeraraghavan, 2018. "Simple Policies for Managing Flexible Capacity," Manufacturing & Service Operations Management, INFORMS, vol. 20(2), pages 333-346, May.
    12. José Niño-Mora, 2006. "Restless Bandit Marginal Productivity Indices, Diminishing Returns, and Optimal Control of Make-to-Order/Make-to-Stock M/G/1 Queues," Mathematics of Operations Research, INFORMS, vol. 31(1), pages 50-84, February.
    13. Dimitris Bertsimas & Ioannis Ch. Paschalidis, 2001. "Probabilistic Service Level Guarantees in Make-to-Stock Manufacturing Systems," Operations Research, INFORMS, vol. 49(1), pages 119-133, February.
    14. David M. Markowitz & Lawrence M. Wein, 2001. "Heavy Traffic Analysis of Dynamic Cyclic Policies: A Unified Treatment of the Single Machine Scheduling Problem," Operations Research, INFORMS, vol. 49(2), pages 246-270, April.
    15. Arreola-Risa, Antonio & Giménez-García, Víctor M. & Martínez-Parra, José Luis, 2011. "Optimizing stochastic production-inventory systems: A heuristic based on simulation and regression analysis," European Journal of Operational Research, Elsevier, vol. 213(1), pages 107-118, August.
    16. 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.
    17. Arts, Joachim, 2017. "A multi-item approach to repairable stocking and expediting in a fluctuating demand environment," European Journal of Operational Research, Elsevier, vol. 256(1), pages 102-115.
    18. Fernando Bernstein & Francis de Véricourt, 2008. "Competition for Procurement Contracts with Service Guarantees," Operations Research, INFORMS, vol. 56(3), pages 562-575, June.
    19. Rezaei Somarin, Aghil & Chen, Songlin & Asian, Sobhan & Wang, David Z.W., 2017. "A heuristic stock allocation rule for repairable service parts," International Journal of Production Economics, Elsevier, vol. 184(C), pages 131-140.
    20. Jian Yang, 2004. "Production Control in the Face of Storable Raw Material, Random Supply, and an Outside Market," Operations Research, INFORMS, vol. 52(2), pages 293-311, April.

    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:50:y:2004:i:10:p:1431-1448. 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.