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Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition

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  • Cheramin, Meysam
  • Saha, Apurba Kumar
  • Cheng, Jianqiang
  • Paul, Sanjoy Kumar
  • Jin, Hongyue

Abstract

Neodymium-iron-boron (NdFeB) magnets are the most powerful magnets per unit volume sold in the commercial market. Despite the increasing demand for clean energy applications such as electric vehicles and wind turbines, disruptive events including the COVID-19 pandemic have caused significant uncertainties in the supply and demand for NdFeB magnets. Therefore, this study aims to alleviate the risk of supply shortage for NdFeB magnets and the containing critical materials, rare-earth elements (REEs), through the development of a resilient reverse supply chain and logistics network design. We develop scenarios to model the unique impact of the COVID-19 pandemic on the proposed business, incorporating both disruption intensity and recovery rate. We formulate a chance-constrained two-stage stochastic programming model to maximize the profit while guaranteeing the network resiliency against disruption risks. To solve the problem in large-scale instances, we develop an efficient Benders decomposition algorithm that reduces the computational time by 98.5% on average compared to the default CPLEX algorithm. When applied to the United States, the model suggests the optimal facility locations, processing capacities, inventory levels, and material flows for NdFeB magnet recyclers that could meet 99.7% of the demand. To the best of our knowledge, this study is the first to incorporate the impacts of the COVID-19 pandemic to design a resilient NdFeB magnet recycling supply chain and logistics network, leveraging risk-averse stochastic programming.

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  • Cheramin, Meysam & Saha, Apurba Kumar & Cheng, Jianqiang & Paul, Sanjoy Kumar & Jin, Hongyue, 2021. "Resilient NdFeB magnet recycling under the impacts of COVID-19 pandemic: Stochastic programming and Benders decomposition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
  • Handle: RePEc:eee:transe:v:155:y:2021:i:c:s1366554521002672
    DOI: 10.1016/j.tre.2021.102505
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    1. Florian Lücker & Ralf W. Seifert & Işık Biçer, 2019. "Roles of inventory and reserve capacity in mitigating supply chain disruption risk," International Journal of Production Research, Taylor & Francis Journals, vol. 57(4), pages 1238-1249, February.
    2. Seyed Mohammad Khalili & Fariborz Jolai & Seyed Ali Torabi, 2017. "Integrated production–distribution planning in two-echelon systems: a resilience view," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1040-1064, February.
    3. Salehi Sadghiani, N. & Torabi, S.A. & Sahebjamnia, N., 2015. "Retail supply chain network design under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 75(C), pages 95-114.
    4. Nagurney, Anna, 2021. "Optimization of supply chain networks with inclusion of labor: Applications to COVID-19 pandemic disruptions," International Journal of Production Economics, Elsevier, vol. 235(C).
    5. Zhalechian, M. & Torabi, S. Ali & Mohammadi, M., 2018. "Hub-and-spoke network design under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 109(C), pages 20-43.
    6. Baghalian, Atefeh & Rezapour, Shabnam & Farahani, Reza Zanjirani, 2013. "Robust supply chain network design with service level against disruptions and demand uncertainties: A real-life case," European Journal of Operational Research, Elsevier, vol. 227(1), pages 199-215.
    7. Scott DuHadway & Steven Carnovale & Benjamin Hazen, 2019. "Understanding risk management for intentional supply chain disruptions: risk detection, risk mitigation, and risk recovery," Annals of Operations Research, Springer, vol. 283(1), pages 179-198, December.
    8. Brian Tomlin, 2006. "On the Value of Mitigation and Contingency Strategies for Managing Supply Chain Disruption Risks," Management Science, INFORMS, vol. 52(5), pages 639-657, May.
    9. Xiaoyue Du & T. E. Graedel, 2011. "Global Rare Earth In‐Use Stocks in NdFeB Permanent Magnets," Journal of Industrial Ecology, Yale University, vol. 15(6), pages 836-843, December.
    10. Ahmed Khassiba & Fabian Bastin & Sonia Cafieri & Bernard Gendron & Marcel Mongeau, 2020. "Two-Stage Stochastic Mixed-Integer Programming with Chance Constraints for Extended Aircraft Arrival Management," Transportation Science, INFORMS, vol. 54(4), pages 897-919, July.
    11. Chowdhury, Priyabrata & Paul, Sanjoy Kumar & Kaisar, Shahriar & Moktadir, Md. Abdul, 2021. "COVID-19 pandemic related supply chain studies: A systematic review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 148(C).
    12. Hasani, Aliakbar & Khosrojerdi, Amirhossein, 2016. "Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 20-52.
    13. Paul, Sanjoy Kumar & Sarker, Ruhul & Essam, Daryl, 2014. "Real time disruption management for a two-stage batch production–inventory system with reliability considerations," European Journal of Operational Research, Elsevier, vol. 237(1), pages 113-128.
    14. Golev, Artem & Scott, Margaretha & Erskine, Peter D. & Ali, Saleem H. & Ballantyne, Grant R., 2014. "Rare earths supply chains: Current status, constraints and opportunities," Resources Policy, Elsevier, vol. 41(C), pages 52-59.
    15. Sarker, Ruhul & Essam, Daryl, 2017. "A quantitative model for disruption mitigation in a supply chainAuthor-Name: Paul, Sanjoy Kumar," European Journal of Operational Research, Elsevier, vol. 257(3), pages 881-895.
    16. Sanjay Mehrotra & Hamed Rahimian & Masoud Barah & Fengqiao Luo & Karolina Schantz, 2020. "A model of supply‐chain decisions for resource sharing with an application to ventilator allocation to combat COVID‐19," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(5), pages 303-320, August.
    17. Rahmaniani, Ragheb & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter, 2017. "The Benders decomposition algorithm: A literature review," European Journal of Operational Research, Elsevier, vol. 259(3), pages 801-817.
    18. Jill E. Hobbs, 2020. "Food supply chains during the COVID‐19 pandemic," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 68(2), pages 171-176, June.
    19. Jafar Namdar & Xueping Li & Rupy Sawhney & Ninad Pradhan, 2018. "Supply chain resilience for single and multiple sourcing in the presence of disruption risks," International Journal of Production Research, Taylor & Francis Journals, vol. 56(6), pages 2339-2360, March.
    20. Alexandre Dolgui & Dmitry Ivanov & Boris Sokolov, 2020. "Reconfigurable supply chain: the X-network," International Journal of Production Research, Taylor & Francis Journals, vol. 58(13), pages 4138-4163, July.
    21. Lin, Cheng-Chang & Wang, Tsai-Hsin, 2011. "Build-to-order supply chain network design under supply and demand uncertainties," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1162-1176, September.
    22. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    23. Fattahi, Mohammad & Govindan, Kannan, 2018. "A multi-stage stochastic program for the sustainable design of biofuel supply chain networks under biomass supply uncertainty and disruption risk: A real-life case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 534-567.
    24. S.A. Torabi & J. Namdar & S.M. Hatefi & F. Jolai, 2016. "An enhanced possibilistic programming approach for reliable closed-loop supply chain network design," International Journal of Production Research, Taylor & Francis Journals, vol. 54(5), pages 1358-1387, March.
    25. Ahmadi-Javid, Amir & Seddighi, Amir Hossein, 2013. "A location-routing problem with disruption risk," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 53(C), pages 63-82.
    26. Gholami-Zanjani, Seyed Mohammad & Klibi, Walid & Jabalameli, Mohammad Saeed & Pishvaee, Mir Saman, 2021. "The design of resilient food supply chain networks prone to epidemic disruptions," International Journal of Production Economics, Elsevier, vol. 233(C).
    27. Maureen S. Golan & Laura H. Jernegan & Igor Linkov, 2020. "Trends and applications of resilience analytics in supply chain modeling: systematic literature review in the context of the COVID-19 pandemic," Environment Systems and Decisions, Springer, vol. 40(2), pages 222-243, June.
    28. Dmitry Ivanov & Ajay Das, 2020. "Coronavirus (COVID-19/SARS-CoV-2) and supply chain resilience: a research note," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 13(1), pages 90-102.
    29. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    30. Anna Nagurney, 2021. "Perishable Food Supply Chain Networks with Labor in the Covid-19 Pandemic," Springer Optimization and Its Applications, in: Ilias S. Kotsireas & Anna Nagurney & Panos M. Pardalos & Arsenios Tsokas (ed.), Dynamics of Disasters, pages 173-193, Springer.
    31. Heckmann, Iris & Comes, Tina & Nickel, Stefan, 2015. "A critical review on supply chain risk – Definition, measure and modeling," Omega, Elsevier, vol. 52(C), pages 119-132.
    32. Burgos, Diana & Ivanov, Dmitry, 2021. "Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    33. Aldrighetti, Riccardo & Battini, Daria & Ivanov, Dmitry & Zennaro, Ilenia, 2021. "Costs of resilience and disruptions in supply chain network design models: A review and future research directions," International Journal of Production Economics, Elsevier, vol. 235(C).
    34. Sanjoy Kumar Paul & Priyabrata Chowdhury, 2020. "Strategies for Managing the Impacts of Disruptions During COVID-19: an Example of Toilet Paper," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(3), pages 283-293, September.
    35. Fattahi, Mohammad & Govindan, Kannan & Keyvanshokooh, Esmaeil, 2017. "Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 101(C), pages 176-200.
    36. Zahiri, Behzad & Zhuang, Jun & Mohammadi, Mehrdad, 2017. "Toward an integrated sustainable-resilient supply chain: A pharmaceutical case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 103(C), pages 109-142.
    37. Lawrence V. Snyder & Zümbül Atan & Peng Peng & Ying Rong & Amanda J. Schmitt & Burcu Sinsoysal, 2016. "OR/MS models for supply chain disruptions: a review," IISE Transactions, Taylor & Francis Journals, vol. 48(2), pages 89-109, February.
    38. Torabi, S.A. & Baghersad, M. & Mansouri, S.A., 2015. "Resilient supplier selection and order allocation under operational and disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 22-48.
    39. Ho-Yin Mak & Zuo-Jun Shen, 2012. "Risk diversification and risk pooling in supply chain design," IISE Transactions, Taylor & Francis Journals, vol. 44(8), pages 603-621.
    40. Jabbarzadeh, Armin & Fahimnia, Behnam & Sheu, Jiuh-Biing & Moghadam, Hani Shahmoradi, 2016. "Designing a supply chain resilient to major disruptions and supply/demand interruptions," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 121-149.
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