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Production planning under uncertainty in textile manufacturing

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  • S Karabuk

    (University of Oklahoma)

Abstract

Textile manufacturing consists of yarn production, fabric formation, and finishing and dyeing stages. The subject of this paper is the yarn production planning problem, although the approach is directly applicable to the fabric production planning problem due to similarities in the respective models. Our experience at an international textile manufacturer indicates that demand uncertainty is a major challenge in developing yarn production plans. We develop a stochastic programming model that explicitly includes uncertainty in the form of discrete demand scenarios. This results in a large-scale mixed integer model that is difficult to solve with off-the-shelf commercial solvers. We develop a two-step preprocessing algorithm that improves the linear programming relaxation of the model and reduces its size, consequently improving the computational requirements. We illustrate the benefits of a stochastic programming approach over a deterministic model and share our initial application experience.

Suggested Citation

  • S Karabuk, 2008. "Production planning under uncertainty in textile manufacturing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(4), pages 510-520, April.
    • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:4:d:10.1057_palgrave.jors.2602370
    DOI: 10.1057/palgrave.jors.2602370
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    References listed on IDEAS

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    Cited by:

    1. Pereira, Daniel Filipe & Oliveira, José Fernando & Carravilla, Maria Antónia, 2023. "Design of a sales plan in a hybrid contractual and non-contractual context in a setting of limited capacity: A robust approach," International Journal of Production Economics, Elsevier, vol. 260(C).
    2. Palmowski, Zbigniew & Sidorowicz, Aleksandra, 2020. "An application of dynamic programming to assign pressing tanks at wineries," European Journal of Operational Research, Elsevier, vol. 287(1), pages 293-305.
    3. Houssem Felfel & Wafa Ben Yahia & Omar Ayadi & Faouzi Masmoudi, 2018. "Stochastic multi-site supply chain planning in textile and apparel industry under demand and price uncertainties with risk aversion," Annals of Operations Research, Springer, vol. 271(2), pages 551-574, December.
    4. M Kazemi Zanjani & M Nourelfath & D Ait-Kadi, 2011. "Production planning with uncertainty in the quality of raw materials: a case in sawmills," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1334-1343, July.
    5. Körpeoglu, Ersin & Yaman, Hande & Selim Aktürk, M., 2011. "A multi-stage stochastic programming approach in master production scheduling," European Journal of Operational Research, Elsevier, vol. 213(1), pages 166-179, August.
    6. Bohle, Carlos & Maturana, Sergio & Vera, Jorge, 2010. "A robust optimization approach to wine grape harvesting scheduling," European Journal of Operational Research, Elsevier, vol. 200(1), pages 245-252, January.

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