IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v200y2010i1p54-62.html
   My bibliography  Save this article

Multi-item inventory control with full truckloads: A comparison of aggregate and individual order triggering

Author

Listed:
  • Kiesmüller, G.P.

Abstract

In this paper, we consider the stochastic joint replenishment problem in an environment where transportation costs are dominant and full truckloads or full container loads are required. One replenishment policy, taking into account capacity restrictions of the total order volume, is the so-called QS policy, where replenishment orders are placed to raise the individual inventory positions of all items to their order-up-to levels, whenever the aggregate inventory position drops below the reorder level. We first provide a method to compute the policy parameters of a QS policy such that item target service levels can be met, under the assumption that demand can be modeled as a compound renewal process. The approximation formulas are based on renewal theory and are tested in a simulation study which reveals good performance. Second, we compare the QS policy with a simple allocation policy where replenishment orders are triggered by the individual inventory positions of the items. At the moment when an individual inventory position drops below its item reorder level, a replenishment order is triggered and the total vehicle capacity is allocated to all items such that the expected elapsed time before the next replenishment order is maximized. In an extensive simulation study it is illustrated that the QS policy outperforms this allocation policy since it results in lower inventory levels for the same service level. Although both policies lead to similar performance if items are identical, it can differ substantially if the item characteristics vary.

Suggested Citation

  • Kiesmüller, G.P., 2010. "Multi-item inventory control with full truckloads: A comparison of aggregate and individual order triggering," European Journal of Operational Research, Elsevier, vol. 200(1), pages 54-62, January.
  • Handle: RePEc:eee:ejores:v:200:y:2010:i:1:p:54-62
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(08)01043-6
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ward Whitt, 1982. "Approximating a Point Process by a Renewal Process, I: Two Basic Methods," Operations Research, INFORMS, vol. 30(1), pages 125-147, February.
    2. Edward Ignall, 1969. "Optimal Continuous Review Policies for Two Product Inventory Systems with Joint Setup Costs," Management Science, INFORMS, vol. 15(5), pages 278-283, January.
    3. A. Federgruen & H. Groenevelt & H. C. Tijms, 1984. "Coordinated Replenishments in a Multi-Item Inventory System with Compound Poisson Demands," Management Science, INFORMS, vol. 30(3), pages 344-357, March.
    4. Joseph L. Balintfy, 1964. "On a Basic Class of Multi-Item Inventory Problems," Management Science, INFORMS, vol. 10(2), pages 287-297, January.
    5. Swenseth, Scott R. & Godfrey, Michael R., 2002. "Incorporating transportation costs into inventory replenishment decisions," International Journal of Production Economics, Elsevier, vol. 77(2), pages 113-130, May.
    6. Derek R. Atkins & Paul O. Iyogun, 1988. "Periodic Versus "Can-Order" Policies for Coordinated Multi-Item Inventory Systems," Management Science, INFORMS, vol. 34(6), pages 791-796, June.
    7. S. Viswanathan, 1997. "Note. Periodic Review (s, S) Policies for Joint Replenishment Inventory Systems," Management Science, INFORMS, vol. 43(10), pages 1447-1454, October.
    8. Schultz, Helle & Johansen, Soren Glud, 1999. "Can-order policies for coordinated inventory replenishment with Erlang distributed times between ordering," European Journal of Operational Research, Elsevier, vol. 113(1), pages 30-41, February.
    9. Goyal, Suresh K. & Satir, Ahmet T., 1989. "Joint replenishment inventory control: Deterministic and stochastic models," European Journal of Operational Research, Elsevier, vol. 38(1), pages 2-13, January.
    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. Padilla Tinoco, Silvia Valeria & Creemers, Stefan & Boute, Robert N., 2017. "Collaborative shipping under different cost-sharing agreements," European Journal of Operational Research, Elsevier, vol. 263(3), pages 827-837.
    2. Kouki, Chaaben & Babai, M. Zied & Jemai, Zied & Minner, Stefan, 2016. "A coordinated multi-item inventory system for perishables with random lifetime," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 226-237.
    3. Larsen, Christian, 2009. "The Q(s,S) control policy for the joint replenishment problem extended to the case of correlation among item-demands," International Journal of Production Economics, Elsevier, vol. 118(1), pages 292-297, March.
    4. S G Johansen & P Melchiors, 2003. "Can-order policy for the periodic-review joint replenishment problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(3), pages 283-290, March.
    5. Kiesmüller, G.P., 2009. "A multi-item periodic replenishment policy with full truckloads," International Journal of Production Economics, Elsevier, vol. 118(1), pages 275-281, March.
    6. Creemers, Stefan & Boute, Robert, 2022. "The joint replenishment problem: Optimal policy and exact evaluation method," European Journal of Operational Research, Elsevier, vol. 302(3), pages 1175-1188.
    7. Nielsen, Christina & Larsen, Christian, 2005. "An analytical study of the Q(s,S) policy applied to the joint replenishment problem," European Journal of Operational Research, Elsevier, vol. 163(3), pages 721-732, June.
    8. Banu Yüksel Özkaya & Ülkü Gürler & Emre Berk, 2006. "The stochastic joint replenishment problem: A new policy, analysis, and insights," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(6), pages 525-546, September.
    9. Melchiors, Philip, 2002. "Calculating can-order policies for the joint replenishment problem by the compensation approach," European Journal of Operational Research, Elsevier, vol. 141(3), pages 587-595, September.
    10. Liu, Liming & Yuan, Xue-Ming, 2000. "Coordinated replenishments in inventory systems with correlated demands," European Journal of Operational Research, Elsevier, vol. 123(3), pages 490-503, June.
    11. Lee, Loo Hay & Chew, Ek Peng, 2005. "A dynamic joint replenishment policy with auto-correlated demand," European Journal of Operational Research, Elsevier, vol. 165(3), pages 729-747, September.
    12. Tsai, Chieh-Yuan & Tsai, Chi-Yang & Huang, Po-Wen, 2009. "An association clustering algorithm for can-order policies in the joint replenishment problem," International Journal of Production Economics, Elsevier, vol. 117(1), pages 30-41, January.
    13. Larsen, Christian, 2019. "A heuristic joint replinishment policy for the case of heterogeneity among items," International Journal of Production Economics, Elsevier, vol. 209(C), pages 164-171.
    14. Dellaert, Nico & van de Poel, Erik, 1996. "Global inventory control in an academic hospital," International Journal of Production Economics, Elsevier, vol. 46(1), pages 277-284, December.
    15. Young Hyeon Yang & Jong Soo Kim, 2020. "An adaptive joint replenishment policy for items with non-stationary demands," Operational Research, Springer, vol. 20(3), pages 1665-1684, September.
    16. Eynan, Amit & Kropp, Dean H., 2007. "Effective and simple EOQ-like solutions for stochastic demand periodic review systems," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1135-1143, August.
    17. Stefanny Ramirez & Laurence H. Brandenburg & Dario Bauso, 2023. "Coordinated Replenishment Game and Learning Under Time Dependency and Uncertainty of the Parameters," Dynamic Games and Applications, Springer, vol. 13(1), pages 326-352, March.
    18. Rosales, Claudia R. & Magazine, Michael & Rao, Uday, 2015. "The 2Bin system for controlling medical supplies at point-of-use," European Journal of Operational Research, Elsevier, vol. 243(1), pages 271-280.
    19. De Moor, Bram J. & Creemers, Stefan & Boute, Robert N., 2023. "Breaking truck dominance in supply chains: Proactive freight consolidation and modal split transport," International Journal of Production Economics, Elsevier, vol. 257(C).
    20. Khouja, Moutaz & Goyal, Suresh, 2008. "A review of the joint replenishment problem literature: 1989-2005," European Journal of Operational Research, Elsevier, vol. 186(1), pages 1-16, 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:eee:ejores:v:200:y:2010:i:1:p:54-62. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.