IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-01998733.html
   My bibliography  Save this paper

Production planning with order acceptance and demand uncertainty

Author

Listed:
  • Tarik Aouam

    (UGENT - Universiteit Gent = Ghent University = Université de Gand)

  • Kobe Geryl
  • Kunal Kumar
  • Nadjib Brahimi

    (Department of Industrial Engineering and Management - American University of Sharjah)

Abstract

Traditional production planning models assume that all orders must be satisfied when capacity is available. In this paper, we analyze the value of providing decision makers with the flexibility to accept or reject orders, when order quantity is uncertain. We introduce this demand flexibility in two production planning problems. The first problem integrates order acceptance in the capacitated lot sizing problem, providing the option to reject an order if it requires a high setup cost and cannot be aggregated with additional orders to take advantage of economies of scale. The second problem integrates order acceptance in the order release planning problem with load-dependent lead times (LDLTs). This problem provides the option to reject an order if it increases the workload causing the delay of other orders due to congestion effects. Robust counterparts of both integrated problems are formulated as linear mixed integer programs (MIPs). The deterministic integrated problems and their robust counterparts are shown to be NP-hard and a two-stage MIP heuristic is proposed as a solution procedure. A relax and fix (RF) heuristic is adapted to efficiently construct feasible solutions to the robust problems, which are then improved by a fix and optimize (FO) heuristic. Numerical results show that the proposed heuristics give promising results in terms of solution quality and computation time. Simulation experiments are conducted to assess the value of demand flexibility and to study the effects of various parameters on economical performance.

Suggested Citation

  • Tarik Aouam & Kobe Geryl & Kunal Kumar & Nadjib Brahimi, 2018. "Production planning with order acceptance and demand uncertainty," Post-Print hal-01998733, HAL.
    • Handle: RePEc:hal:journl:hal-01998733
    DOI: 10.1016/j.cor.2017.11.013
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Rakiz, Asma & Absi, Nabil & Fenies, Pierre, 2023. "Comparing approaches for a multi-level planning problem in a mining industry," International Journal of Production Economics, Elsevier, vol. 265(C).
    2. Ghadimi, Foad & Aouam, Tarik & Haeussler, Stefan & Uzsoy, Reha, 2022. "Integrated and hierarchical systems for coordinating order acceptance and release planning," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1277-1289.
    3. Absi, Nabil & van den Heuvel, Wilco, 2019. "Worst case analysis of Relax and Fix heuristics for lot-sizing problems," European Journal of Operational Research, Elsevier, vol. 279(2), pages 449-458.
    4. Pereira, Daniel Filipe & Oliveira, José Fernando & Carravilla, Maria Antónia, 2020. "Tactical sales and operations planning: A holistic framework and a literature review of decision-making models," International Journal of Production Economics, Elsevier, vol. 228(C).
    5. Durdu Hakan Utku, 2023. "The Evaluation and Improvement of the Production Processes of an Automotive Industry Company via Simulation and Optimization," Sustainability, MDPI, vol. 15(3), pages 1-17, January.
    6. Bachler, Sebastian & Haeussler, Stefan & Momsen, Katharina & Stefan, Matthias, 2024. "Do people willfully ignore decision support? Evidence from an online experiment," VfS Annual Conference 2024 (Berlin): Upcoming Labor Market Challenges 302404, Verein für Socialpolitik / German Economic Association.
    7. Kajjoune, Oussama & Aouam, Tarik & Zouadi, Tarik & Ranjan, Ravi Prakash, 2023. "Dynamic lot-sizing in a two-stage supply chain with liquidity constraints and financing options," International Journal of Production Economics, Elsevier, vol. 258(C).
    8. Junzo Watada & Nureize Binti Arbaiy & Qiuhong Chen, 2021. "Hybrid Uncertainty-Goal Programming Model with Scaled Index for Production Planning Assessment," FinTech, MDPI, vol. 1(1), pages 1-24, November.

    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:hal:journl:hal-01998733. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.