A location-allocation model for sustainable NdFeB magnet recovery under uncertainties

Hongyue Jin; Byung Duk Song; Gamini Mendis; Yuehwern Yih; John W. Sutherland

doi:10.1016/j.cirp.2018.04.050

A location-allocation model for sustainable NdFeB magnet recovery under uncertainties

Hongyue Jin, Byung Duk Song, Gamini Mendis, Yuehwern Yih, John W. Sutherland

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

Neodymium-iron-boron (NdFeB) magnets play a critical role in clean power products, e.g., electric vehicles and wind turbines. Since China has near monopolistic control of the supply of these magnets, many parties are interested in recovering end-of-life magnets for additional use cycles. Such a strategy requires a cost-effective approach to collect and process used magnets while maximizing the economic and environmental benefits. This paper employs fuzzy logic and non-dominated sorting genetic algorithm (NSGA-II) to solve a location-allocation problem for NdFeB magnet recovery under supply and demand uncertainties. A Pareto front is constructed to evaluate the performance of the proposed design.

Original language	English (US)
Pages (from-to)	37-40
Number of pages	4
Journal	CIRP Annals
Volume	67
Issue number	1
DOIs	https://doi.org/10.1016/j.cirp.2018.04.050
State	Published - Jan 1 2018
Externally published	Yes

Keywords

Design optimization
Genetic modelling
Logistics

ASJC Scopus subject areas

Mechanical Engineering
Industrial and Manufacturing Engineering

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10.1016/j.cirp.2018.04.050

Cite this

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abstract = "Neodymium-iron-boron (NdFeB) magnets play a critical role in clean power products, e.g., electric vehicles and wind turbines. Since China has near monopolistic control of the supply of these magnets, many parties are interested in recovering end-of-life magnets for additional use cycles. Such a strategy requires a cost-effective approach to collect and process used magnets while maximizing the economic and environmental benefits. This paper employs fuzzy logic and non-dominated sorting genetic algorithm (NSGA-II) to solve a location-allocation problem for NdFeB magnet recovery under supply and demand uncertainties. A Pareto front is constructed to evaluate the performance of the proposed design.",

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AU - Jin, Hongyue

AU - Song, Byung Duk

AU - Mendis, Gamini

AU - Yih, Yuehwern

AU - Sutherland, John W.

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AB - Neodymium-iron-boron (NdFeB) magnets play a critical role in clean power products, e.g., electric vehicles and wind turbines. Since China has near monopolistic control of the supply of these magnets, many parties are interested in recovering end-of-life magnets for additional use cycles. Such a strategy requires a cost-effective approach to collect and process used magnets while maximizing the economic and environmental benefits. This paper employs fuzzy logic and non-dominated sorting genetic algorithm (NSGA-II) to solve a location-allocation problem for NdFeB magnet recovery under supply and demand uncertainties. A Pareto front is constructed to evaluate the performance of the proposed design.

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A location-allocation model for sustainable NdFeB magnet recovery under uncertainties

Abstract

Keywords

ASJC Scopus subject areas

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