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Stochastic multi-site supply chain planning in textile and apparel industry under demand and price uncertainties with risk aversion

Author

Listed:
  • Houssem Felfel

    (University of Sfax, National Engineering School of Sfax (ENIS))

  • Wafa Ben Yahia

    (University of Sfax, National Engineering School of Sfax (ENIS))

  • Omar Ayadi

    (University of Sfax, National Engineering School of Sfax (ENIS))

  • Faouzi Masmoudi

    (University of Sfax, National Engineering School of Sfax (ENIS))

Abstract

A multi-product, multi-period, multi-site supply chain production and transportation planning problem, in the textile and apparel industry, under demand and price uncertainties is considered in this paper. The problem is formulated using a two-stage stochastic programming model taking into account the production amount, the inventory and backorder levels as well as the amounts of products to be transported between the different plants and customers in each period. Risk management is addressed by incorporating a risk measure into the stochastic programming model as a second objective function, which leads to a multi-objective optimization model. The objectives aim to simultaneously maximize the expected net profit and minimize the financial risk measured. Two risk measures are compared: the conditional-value-at-risk and the downside risk. As the considered objective functions conflict with each other’s, the problem solution is a front of Pareto optimal robust alternatives, which represents the trade-off among the different objective functions. A case study using real data from textile and apparel industry in Tunisia is presented to illustrate the effectiveness of the proposed model and the robustness of the obtained solutions.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:271:y:2018:i:2:d:10.1007_s10479-018-2980-2
    DOI: 10.1007/s10479-018-2980-2
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. M. J. Hermoso-Orzáez & J. Garzón-Moreno, 2022. "Risk management methodology in the supply chain: a case study applied," Annals of Operations Research, Springer, vol. 313(2), pages 1051-1075, June.
    2. J. F. F. Almeida & S. V. Conceição & L. R. Pinto & B. R. P. Oliveira & L. F. Rodrigues, 2022. "Optimal sales and operations planning for integrated steel industries," Annals of Operations Research, Springer, vol. 315(2), pages 773-790, August.

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