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Closed-loop supply chain network design and modelling under risks and demand uncertainty: an integrated robust optimization approach

Author

Listed:
  • Surya Prakash

    (BML Munjal University)

  • Sameer Kumar

    (University of St. Thomas)

  • Gunjan Soni

    (Malaviya National Institute of Technology)

  • Vipul Jain

    (Victoria University of Wellington)

  • Ajay Pal Singh Rathore

    (Malaviya National Institute of Technology)

Abstract

Closed loop supply chain network design (CL-SCND) is a critical economic and environmental activity. The closing of the loop to handle return, uncertainty in business environment, various supply chain risks, impact network design processes and performance of the firm in the long term. Thus, it is important to design robust and reliable supply chain structures and obtain network configurations which can always outperform the other configurations under the worst cases of risks and uncertainty. A generic closed-loop supply chain network based on mixed integer programming formulation is proposed with direct shipping to the customer from manufacturing plants as well as shipping through distribution centers under supply risks, transportation risk and uncertain demand using a robust optimization (RO) approach. A large number of numerical tests are carried out to test the performance of the model by considering a total of four levels of uncertainty for four different network structures types. The results of the tests confirm that the risk and uncertainty based integrated supply chain network models are more efficient (cost effective) than the other set of network configurations which treats the supply chain risks and uncertainty post-ante. To demonstrate the applicability of the proposed model, the case of an Indian e-commerce firm which wants to redesign its supply chain structure is presented. The results of case study show that the topology obtained from integrated treatment of risk and uncertainty called as RORU model, outperform other supply chain networks on various network performance indicators such as supply chain costs, the number of facilities open or close and the amount of products flowing through supply chain echelon. Thus, RO based mathematical modeling to address risks and its applicability for SCND for close loop supply chain is proposed, demonstrated and applied in practical cases.

Suggested Citation

  • Surya Prakash & Sameer Kumar & Gunjan Soni & Vipul Jain & Ajay Pal Singh Rathore, 2020. "Closed-loop supply chain network design and modelling under risks and demand uncertainty: an integrated robust optimization approach," Annals of Operations Research, Springer, vol. 290(1), pages 837-864, July.
    • Handle: RePEc:spr:annopr:v:290:y:2020:i:1:d:10.1007_s10479-018-2902-3
    DOI: 10.1007/s10479-018-2902-3
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    3. Pin, Lantos A. & Pennink, Bartjan J.W. & Balsters, Herman & Sianipar, Corinthias P.M., 2021. "Technological appropriateness of biomass production in rural settings: Addressing water hyacinths (E. crassipes) problem in Lake Tondano, Indonesia," Technology in Society, Elsevier, vol. 66(C).
    4. 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).
    5. Rimalini Gadekar & Bijan Sarkar & Ashish Gadekar, 2022. "Key performance indicator based dynamic decision-making framework for sustainable Industry 4.0 implementation risks evaluation: reference to the Indian manufacturing industries," Annals of Operations Research, Springer, vol. 318(1), pages 189-249, November.
    6. Wang, Xue-Chao & Jiang, Peng & Yang, Lan & Fan, Yee Van & Klemeš, Jiří Jaromír & Wang, Yutao, 2021. "Extended water-energy nexus contribution to environmentally-related sustainable development goals," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    7. Zhou, Yongyi & Zhang, Yulin & Wahab, M.I.M. & Goh, Mark, 2023. "Channel leadership and performance for a closed-loop supply chain considering competition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    8. Mingqiang Yin & Min Huang & Xiaohu Qian & Dazhi Wang & Xingwei Wang & Loo Hay Lee, 2023. "Fourth-party logistics network design with service time constraint under stochastic demand," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1203-1227, March.
    9. Luttiely Santos Oliveira & Ricardo Luiz Machado, 2021. "Application of optimization methods in the closed-loop supply chain: a literature review," Journal of Combinatorial Optimization, Springer, vol. 41(2), pages 357-400, February.
    10. Yang Hu, 2023. "Perspectives in closed-loop supply chains network design considering risk and uncertainty factors," Papers 2306.04819, arXiv.org.
    11. Jose Alejandro Cano & Abraham Londoño-Pineda & Maria Fanny Castro & Hugo Bécquer Paz & Carolina Rodas & Tatiana Arias, 2022. "A Bibliometric Analysis and Systematic Review on E-Marketplaces, Open Innovation, and Sustainability," Sustainability, MDPI, vol. 14(9), pages 1-42, May.

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