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Inventory reservation and real-time order promising in a Make-to-Stock system

In: Supply Chain Planning

Author

Listed:
  • Richard Pibernik

    (International University Schloss Reichartshausen, Supply Management Institute)

  • Prashant Yadav

    (Zaragoza Logistics Center)

Abstract

In this paper we consider a Make-to-Stock order fulfillment system facing random demand with random due date preferences from two classes of customers.We develop an integrated approach for reserving inventory in anticipation of future order arrivals from high priority customers and for order promising in real-time. Our research exhibits three distinct features: (1) we explicitly model uncertain due date preferences of the customers; (2) we consider multiple receipts in the planning horizon that can be utilized to fulfill customer orders; and (3) we choose to utilize a service level measure for reserving inventory rather than estimating short- and long-term implications of order promising with a penalty cost function. We propose an algorithm that exploits the time structure in order arrivals and time-phased material receipts to determine inventory reservations for high priority orders. Numerical experiments are conducted to investigate the performance and the benefits of the inventory reservation and order promising approach under varying system parameters.

Suggested Citation

  • Richard Pibernik & Prashant Yadav, 2009. "Inventory reservation and real-time order promising in a Make-to-Stock system," Springer Books, in: Herbert Meyr & Hans-Otto Günther (ed.), Supply Chain Planning, pages 169-195, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-93775-3_7
    DOI: 10.1007/978-3-540-93775-3_7
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    Citations

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    Cited by:

    1. Secil Savasaneril & Ece Sayin, 2017. "Dynamic lead time quotation under responsive inventory and multiple customer classes," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 95-135, January.
    2. Seitz, Alexander & Grunow, Martin & Akkerman, Renzo, 2020. "Data driven supply allocation to individual customers considering forecast bias," International Journal of Production Economics, Elsevier, vol. 227(C).
    3. Samii, Amir-Behzad & Pibernik, Richard & Yadav, Prashant, 2011. "An inventory reservation problem with nesting and fill rate-based performance measures," International Journal of Production Economics, Elsevier, vol. 133(1), pages 393-402, September.
    4. Ben Ali, M. & D’Amours, S. & Gaudreault, J. & Carle, M-A., 2018. "Configuration and evaluation of an integrated demand management process using a space-filling design and Kriging metamodeling," Operations Research Perspectives, Elsevier, vol. 5(C), pages 45-58.
    5. Ojha, Divesh & Sahin, Funda & Shockley, Jeff & Sridharan, Sri V., 2019. "Is there a performance tradeoff in managing order fulfillment and the bullwhip effect in supply chains? The role of information sharing and information type," International Journal of Production Economics, Elsevier, vol. 208(C), pages 529-543.
    6. Fleischmann, Moritz & Kloos, Konstantin & Nouri, Maryam & Pibernik, Richard, 2020. "Single-period stochastic demand fulfillment in customer hierarchies," European Journal of Operational Research, Elsevier, vol. 286(1), pages 250-266.
    7. Raul Oltra-Badenes & Hermenegildo Gil-Gomez & Jose M Merigo & Daniel Palacios-Marques, 2019. "Methodology and model-based DSS to managing the reallocation of inventory to orders in LHP situations. Application to the ceramics sector," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-19, July.

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