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A multi-objective formulation for the closed-loop plastic supply chain under uncertainty

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  • Seyed Babak Ebrahimi

    (K. N. Toosi University of Technology)

  • Ehsan Bagheri

    (K. N. Toosi University of Technology)

Abstract

Supply risk is one of the undeniable risks in a supply chain that can affect the supply chain process and lead to disruptions in customer satisfaction or distributor reliability. This research employs a closed-loop supply chain network for the plastic bottle industry, followed by formulating a multi-objective mathematical model by considering several assumptions. The model seeks to optimize total costs, supply risk, and customers’ satisfaction (distributor’s reliability). The revised multi-choice goal programming approach is also applied to solve the model and verify it through a case study. Moreover, the best–worst method as a robust multi-criteria decision-making tool is used to find the values of the parameters of supply risk. Afterward, the sensitivity analysis checks the proposed framework’s robustness and shows its reaction under various conditions. Our results indicate the effectiveness of the proposed framework and offer insights that can be used to improve an organization’s status.

Suggested Citation

  • Seyed Babak Ebrahimi & Ehsan Bagheri, 2022. "A multi-objective formulation for the closed-loop plastic supply chain under uncertainty," Operational Research, Springer, vol. 22(5), pages 4725-4768, November.
    • Handle: RePEc:spr:operea:v:22:y:2022:i:5:d:10.1007_s12351-022-00716-y
    DOI: 10.1007/s12351-022-00716-y
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    1. Hsu, Chaug-Ing & Li, Hui-Chieh, 2011. "Reliability evaluation and adjustment of supply chain network design with demand fluctuations," International Journal of Production Economics, Elsevier, vol. 132(1), pages 131-145, July.
    2. Feng, Xuehao & Moon, Ilkyeong & Ryu, Kwangyeol, 2014. "Revenue-sharing contracts in an N-stage supply chain with reliability considerations," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 20-29.
    3. He, Qing & Liu, Junyi & Gan, Jingyun & Qian, Zongxin, 2019. "Systemic financial risk and macroeconomic activity in China," Journal of Economics and Business, Elsevier, vol. 102(C), pages 57-63.
    4. Bimal Kumar Mawandiya & J. K. Jha & Jitesh J. Thakkar, 2020. "Optimal production-inventory policy for closed-loop supply chain with remanufacturing under random demand and return," Operational Research, Springer, vol. 20(3), pages 1623-1664, September.
    5. Raghu Nandan Giri & Shyamal Kumar Mondal & Manoranjan Maiti, 2021. "Analysis of strategies for substitutable and complementary products in a two-levels fuzzy supply chain system," Operational Research, Springer, vol. 21(1), pages 485-524, March.
    6. Stoutenborough, James W. & Vedlitz, Arnold, 2016. "The role of scientific knowledge in the public's perceptions of energy technology risks," Energy Policy, Elsevier, vol. 96(C), pages 206-216.
    7. Abdul Sattar Safaei & Saba Farsad & Mohammad Mahdi Paydar, 2020. "Emergency logistics planning under supply risk and demand uncertainty," Operational Research, Springer, vol. 20(3), pages 1437-1460, September.
    8. He, Yuanjie, 2017. "Supply risk sharing in a closed-loop supply chain," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 39-52.
    9. Yu, Chian-Son & Li, Han-Lin, 2000. "A robust optimization model for stochastic logistic problems," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 385-397, March.
    10. A. Charnes & W. W. Cooper, 1957. "Management Models and Industrial Applications of Linear Programming," Management Science, INFORMS, vol. 4(1), pages 38-91, October.
    11. Gouveia, Luis, 1996. "Multicommodity flow models for spanning trees with hop constraints," European Journal of Operational Research, Elsevier, vol. 95(1), pages 178-190, November.
    12. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    13. G Barbarosoǧlu & Y Arda, 2004. "A two-stage stochastic programming framework for transportation planning in disaster response," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(1), pages 43-53, January.
    14. Aharon Ben-Tal & Dimitris Bertsimas & David B. Brown, 2010. "A Soft Robust Model for Optimization Under Ambiguity," Operations Research, INFORMS, vol. 58(4-part-2), pages 1220-1234, August.
    15. Rezaei, Jafar, 2015. "Best-worst multi-criteria decision-making method," Omega, Elsevier, vol. 53(C), pages 49-57.
    16. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
    17. Romero, Carlos, 2001. "Extended lexicographic goal programming: a unifying approach," Omega, Elsevier, vol. 29(1), pages 63-71, February.
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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.

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