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Combined make-to-order/make-to-stock supply chains

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  • Philip Kaminsky
  • Onur Kaya

Abstract

A multi-item manufacturer served by a single supplier in a stochastic environment is considered. The manufacturer and the supplier have to decide which items to produce to stock and which to produce to order. The manufacturer also has to quote due dates to arriving customers for make-to-order products. The manufacturer is penalized for long lead times, missing the quoted lead times and high inventory levels. Several variations of this problem are considered and effective heuristics for the make-to-order/make-to stock decision are designed to find the appropriate inventory levels for make-to-stock items. Scheduling and lead time quotation algorithms for centralized and decentralized versions of the model are also developed. Extensive computational testing is performed to assess the effectiveness of the proposed algorithms, and the centralized and decentralized models are compared in order to quantify the value of centralized control in this supply chain. As centralized control is not always practical or cost-effective, the value of limited information exchange for this system is explored.[Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following free supplemental resource(s): Online appendix including additional computational analysis and proofs.]

Suggested Citation

  • Philip Kaminsky & Onur Kaya, 2009. "Combined make-to-order/make-to-stock supply chains," IISE Transactions, Taylor & Francis Journals, vol. 41(2), pages 103-119.
    • Handle: RePEc:taf:uiiexx:v:41:y:2009:i:2:p:103-119
    DOI: 10.1080/07408170801975065
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    Citations

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    Cited by:

    1. Agra, Agostinho & Poss, Michael & Santos, Micael, 2018. "Optimizing make-to-stock policies through a robust lot-sizing model," International Journal of Production Economics, Elsevier, vol. 200(C), pages 302-310.
    2. Talay, Işılay & Özdemir-Akyıldırım, Öznur, 2019. "Optimal procurement and production planning for multi-product multi-stage production under yield uncertainty," European Journal of Operational Research, Elsevier, vol. 275(2), pages 536-551.
    3. Wei-Shiun Chang & Daniel A. Sanchez-Loor, 2020. "Downstream Information Leaking and Information Sharing Between Partially Informed Retailers," Journal of Industry, Competition and Trade, Springer, vol. 20(4), pages 733-760, December.
    4. Alexander Seitz & Martin Grunow, 2017. "Increasing accuracy and robustness of order promises," International Journal of Production Research, Taylor & Francis Journals, vol. 55(3), pages 656-670, February.
    5. 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.
    6. Ghasemi, Elaheh & Lehoux, Nadia & Rönnqvist, Mikael, 2024. "A multi-level production-inventory-distribution system under mixed make to stock, make to order, and vendor managed inventory strategies: An application in the pulp and paper industry," International Journal of Production Economics, Elsevier, vol. 271(C).
    7. Xin, Linwei & Goldberg, David A., 2021. "Time (in)consistency of multistage distributionally robust inventory models with moment constraints," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1127-1141.

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