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A stochastic closed-loop supply chain network design problem with multiple recovery options

Author

Listed:
  • Zied Jemai

    (LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec)

  • Rim Jerbia

    (OASIS - Optimisation des systèmes industriels et de services [Tunis] - ENIT - Ecole Nationale d'Ingénieurs de Tunis - UTM - Université de Tunis El Manar)

  • Mouna Kchaou Boujelben

    (UAEU - United Arab Emirates University)

  • Mohamed Amine Sehli

    (OASIS - Optimisation des systèmes industriels et de services [Tunis] - ENIT - Ecole Nationale d'Ingénieurs de Tunis - UTM - Université de Tunis El Manar)

  • Mohamed Amine Sehli

Abstract

In this paper, a closed-loop supply chain network design problem with multiple recovery options is studied. First, the deterministic problem is formulated as a Mixed Integer Linear Program (MILP). A sensitivity analysis is carried out in order to investigate the impact of variations of the main input parameters such as customer return rates, revenues, costs as well as the proportions of returns assigned to each recovery option, on the network structure and the company profit. Then, a stochastic version of the model is developed to account for the high uncertainties faced by companies. A scenario-based approach is used to model the uncertainties of return rates, revenues, costs and the quality of returns. The computational results show that the solution of the stochastic problem is stable over different replications and that the benefit from using stochastic modeling increases when the penalty over non collected returns increases.

Suggested Citation

  • Zied Jemai & Rim Jerbia & Mouna Kchaou Boujelben & Mohamed Amine Sehli & Mohamed Amine Sehli, 2018. "A stochastic closed-loop supply chain network design problem with multiple recovery options," Post-Print hal-01742193, HAL.
    • Handle: RePEc:hal:journl:hal-01742193
    DOI: 10.1016/j.cie.2018.02.011
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    Citations

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    Cited by:

    1. Yufei Hu & Lianghua Chen & Yingying Chi & Bowen Song, 2022. "Manufacturer encroachment on a closed‐loop supply chain with design for remanufacturing," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 1941-1959, September.
    2. Jian Zhou & Wenying Xia & Ke Wang & Hui Li & Qianyu Zhang, 2020. "Fuzzy Bi-Objective Closed-Loop Supply Chain Network Design Problem with Multiple Recovery Options," Sustainability, MDPI, vol. 12(17), pages 1-26, August.
    3. Guanshuang Jiang & Qi Wang & Ke Wang & Qianyu Zhang & Jian Zhou, 2020. "A Novel Closed-Loop Supply Chain Network Design Considering Enterprise Profit and Service Level," Sustainability, MDPI, vol. 12(2), pages 1-21, January.
    4. Shraddha Mishra & Surya Prakash Singh, 2022. "Designing dynamic reverse logistics network for post-sale service," Annals of Operations Research, Springer, vol. 310(1), pages 89-118, March.
    5. Magdalena Rusch & Josef‐Peter Schöggl & Rupert J. Baumgartner, 2023. "Application of digital technologies for sustainable product management in a circular economy: A review," Business Strategy and the Environment, Wiley Blackwell, vol. 32(3), pages 1159-1174, March.
    6. Simonetto, Marco & Sgarbossa, Fabio & Battini, Daria & Govindan, Kannan, 2022. "Closed loop supply chains 4.0: From risks to benefits through advanced technologies. A literature review and research agenda," International Journal of Production Economics, Elsevier, vol. 253(C).
    7. YoungSu Yun & Anudari Chuluunsukh & Mitsuo Gen, 2020. "Sustainable Closed-Loop Supply Chain Design Problem: A Hybrid Genetic Algorithm Approach," Mathematics, MDPI, vol. 8(1), pages 1-19, January.
    8. Ali Pedram & Shahryar Sorooshian & Freselam Mulubrhan & Afshin Abbaspour, 2023. "Incorporating Vehicle-Routing Problems into a Closed-Loop Supply Chain Network Using a Mixed-Integer Linear-Programming Model," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    9. Diabat, Ali & Jebali, Aida, 2021. "Multi-product and multi-period closed loop supply chain network design under take-back legislation," International Journal of Production Economics, Elsevier, vol. 231(C).
    10. Reddy, K. Nageswara & Kumar, Akhilesh & Choudhary, Alok & Cheng, T. C. Edwin, 2022. "Multi-period green reverse logistics network design: An improved Benders-decomposition-based heuristic approach," European Journal of Operational Research, Elsevier, vol. 303(2), pages 735-752.
    11. Yang Hu, 2023. "Perspectives in closed-loop supply chains network design considering risk and uncertainty factors," Papers 2306.04819, arXiv.org.

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