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Robust demand service achievement for the co-production newsvendor

Author

Listed:
  • Tsan Ng
  • John Fowler
  • Ivy Mok

Abstract

The co-production newsvendor problem is motivated by two-stage production processes that simultaneously yield a set of output products of different grades from the same input stocks. Co-production is a characteristic feature of processes such as semiconductor manufacturing and crude oil distillation. In the first stage, the newsvendor executes the order quantities for the input stocks prior to learning the actual demands and grading fractions of the products. In the second stage, the available production is allocated to satisfy the realized demands. Downward substitution is allowed in the allocation; i.e., demands for lower grades can always be filled by higher grades but not vice versa. The co-production newsvendor seeks to achieve maximum demand service level, subject to resource or budget constraints. This article proposes the use of the aspiration level approach to model the decision problem. Furthermore, it is assumed that only the means and supports of the uncertain demands and grading fractions are available, and the model is extended using robust optimization techniques. The resulting model is a linear program and can be solved very efficiently. Computational tests show that the proposed model performs favorably compared to other stochastic optimization approaches for the same problem.

Suggested Citation

  • Tsan Ng & John Fowler & Ivy Mok, 2012. "Robust demand service achievement for the co-production newsvendor," IISE Transactions, Taylor & Francis Journals, vol. 44(5), pages 327-341.
  • Handle: RePEc:taf:uiiexx:v:44:y:2012:i:5:p:327-341
    DOI: 10.1080/0740817X.2011.587865
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    Cited by:

    1. Janssen, Larissa & Claus, Thorsten & Sauer, Jürgen, 2016. "Literature review of deteriorating inventory models by key topics from 2012 to 2015," International Journal of Production Economics, Elsevier, vol. 182(C), pages 86-112.
    2. Mengshi Lu & Zuo‐Jun Max Shen, 2021. "A Review of Robust Operations Management under Model Uncertainty," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1927-1943, June.
    3. Ying-Ju Chen & Brian Tomlin & Yimin Wang, 2017. "Dual Coproduct Technologies: Implications for Process Development and Adoption," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 692-712, October.
    4. Onur Boyabatlı, 2015. "Supply Management in Multiproduct Firms with Fixed Proportions Technology," Management Science, INFORMS, vol. 61(12), pages 3013-3031, December.
    5. Kena Zhao & Tsan Sheng (Adam) Ng & Harn Wei Kua & Muchen Tang, 2017. "Modeling environmental impacts and risk under data uncertainties," IISE Transactions, Taylor & Francis Journals, vol. 49(12), pages 1150-1159, December.
    6. Ying-Ju Chen & Brian Tomlin & Yimin Wang, 2013. "Coproduct Technologies: Product Line Design and Process Innovation," Management Science, INFORMS, vol. 59(12), pages 2772-2789, December.
    7. Mohammad Ebrahim Arbabian & Shi Chen & Kamran Moinzadeh, 2021. "Capacity Expansions with Bundled Supplies of Attributes: An Application to Server Procurement in Cloud Computing," Manufacturing & Service Operations Management, INFORMS, vol. 23(1), pages 191-209, 1-2.
    8. He, Shuang & Zhang, Jian & Zhang, Juliang & Cheng, T.C.E., 2022. "Production/inventory competition between firms with fixed-proportions co-production systems," European Journal of Operational Research, Elsevier, vol. 299(2), pages 497-509.

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