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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
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    Citations

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    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. 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).
    4. 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.
    5. 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.
    6. 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).
    7. 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.

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