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Fuzzy Bi-Objective Closed-Loop Supply Chain Network Design Problem with Multiple Recovery Options

Author

Listed:
  • Jian Zhou

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Wenying Xia

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Ke Wang

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Hui Li

    (School of Management, Shanghai University, Shanghai 200444, China)

  • Qianyu Zhang

    (School of Management, Shanghai University, Shanghai 200444, China)

Abstract

A network design of a closed-loop supply chain (CLSC) with multiple recovery modes under fuzzy environments is studied in this article, in which all the cost coefficients (e.g., for facility establishment, transportation, manufacturing and recovery), customer demands, delivery time, recovery rates and some other factors that cannot be precisely estimated while designing are modeled as triangular fuzzy numbers. To handle these uncertain factors and achieve a compromise between the two conflicting objectives of maximizing company profit and improving customer satisfaction, a fuzzy bi-objective programming model and a corresponding two-stage fuzzy interactive solution method are presented. Applying the fuzzy expected value operator and fuzzy ranking method, the fuzzy model is transformed into a deterministic counterpart. Subsequently, Pareto optimal solutions are determined by employing the fuzzy interactive solution method to deal with the conflicting objectives. Numerical experiments address the efficiency of the proposed model and its solution approach. Furthermore, by comparing these results with the CLSC network design in deterministic environments, the benefits of modeling the CLSC network design problem with fuzzy information are highlighted.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:17:p:6770-:d:401850
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    References listed on IDEAS

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    1. 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.
    2. Halit Üster & Sung Ook Hwang, 2017. "Closed-Loop Supply Chain Network Design Under Demand and Return Uncertainty," Transportation Science, INFORMS, vol. 51(4), pages 1063-1085, November.
    3. Lixin Tang & Wei Jiang & Georgios Saharidis, 2013. "An improved Benders decomposition algorithm for the logistics facility location problem with capacity expansions," Annals of Operations Research, Springer, vol. 210(1), pages 165-190, November.
    4. Jimenez, Mariano & Arenas, Mar & Bilbao, Amelia & Rodri'guez, M. Victoria, 2007. "Linear programming with fuzzy parameters: An interactive method resolution," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1599-1609, March.
    5. Jyoti Dhingra Darbari & Devika Kannan & Vernika Agarwal & P. C. Jha, 2019. "Fuzzy criteria programming approach for optimising the TBL performance of closed loop supply chain network design problem," Annals of Operations Research, Springer, vol. 273(1), pages 693-738, February.
    6. Jeihoonian, Mohammad & Kazemi Zanjani, Masoumeh & Gendreau, Michel, 2016. "Accelerating Benders decomposition for closed-loop supply chain network design: Case of used durable products with different quality levels," European Journal of Operational Research, Elsevier, vol. 251(3), pages 830-845.
    7. 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.
    8. Kalpit Patne & Nagesh Shukla & Senevi Kiridena & Manoj Kumar Tiwari, 2018. "Solving closed-loop supply chain problems using game theoretic particle swarm optimisation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5836-5853, September.
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    Cited by:

    1. Yang Hu, 2023. "Perspectives in closed-loop supply chains network design considering risk and uncertainty factors," Papers 2306.04819, arXiv.org.
    2. Yang, Y. & Lin, J. & Hedenstierna, C.P.T. & Zhou, L., 2023. "The more the better? The impact of the number and location of product recovery options on the system dynamics in a closed-loop supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    3. Roy Setiawan & Rabia Salman & Bari Galimovich Khairov & Valeriy Vasilyevich Karpov & Svetlana Dmitrievna Danshina & Lidia Vladimirovna Vasyutkina & Natalia Alekseevna Prodanova & Viacheslav Zhenzhebir, 2021. "Sustainable Closed-Loop Mask Supply Chain Network Design Using Mathematical Modeling and a Fuzzy Multi-Objective Approach," Sustainability, MDPI, vol. 13(10), pages 1-12, May.

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