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

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

doi:10.1016/j.tre.2021.102505

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

Journal Article · Fri Oct 08 00:00:00 EDT 2021 · Transportation Research Part E: Logistics and Transportation Review

DOI:https://doi.org/10.1016/j.tre.2021.102505· OSTI ID:1981781

Cheramin, Meysam ^[1]; Saha, Apurba Kumar ^[1]; Cheng, Jianqiang ^[1]; Paul, Sanjoy Kumar ^[2]; Jin, Hongyue ^[1]

University of Arizona, Tucson, AZ (United States)
University of Technology Sydney, Sydney (Australia)

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.

View Accepted Manuscript (DOE)

Research Organization:: Ames Laboratory (AMES), Ames, IA (United States); University of Arizona, Tucson, AZ (United States)

Sponsoring Organization:: National Institute for Transportation and Communities (NITC); USDOE Office of Energy Efficiency and Renewable Energy (EERE)

Grant/Contract Number:: AC02-07CH11358

OSTI ID:: 1981781

Journal Information:: Transportation Research Part E: Logistics and Transportation Review, Journal Name: Transportation Research Part E: Logistics and Transportation Review Journal Issue: C Vol. 155; ISSN 1366-5545

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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42 ENGINEERING
COVID-19 pandemic
benders decomposition
rare earth magnet
reverse logistics
stochastic programming
supply chain optimization

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

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