Stochastic optimization of value recovery network for Li-ion batteries in the United States under price and return volume uncertainties

Apurba Kumar Saha, Hongyue Jin

Research output: Contribution to journalArticlepeer-review

Abstract

Recycling waste LIBs can be a promising option to tackle the increasing demand of Li-ion batteries (LIBs) in the United States due to the electric vehicle boom and transition towards clean energy. However, the recycling infrastructure is in its infancy in the United States, and there are inherent uncertainties in the collection volume of waste LIBs and the recovered material value that may hinder the path toward sustainable operations. The goal of this study is to maximize the recycling profit of a reverse logistics supply chain network developed considering uncertainties in feedstock volume and sales price as well as other economic challenges unique to the US market. In this study, a two-stage stochastic model is proposed to facilitate strategic decision-making. Additionally, this study quantifies the impact of uncertainties on recycling operations and government policies adopted to promote large-scale recycling of waste LIB materials in the US.

Original languageEnglish (US)
Article number107623
JournalResources, Conservation and Recycling
Volume206
DOIs
StatePublished - Jul 2024
Externally publishedYes

Keywords

  • Critical materials
  • Government policy
  • Recycling
  • Reverse logistics
  • Sample average approximation
  • Two-stage stochastic programming

ASJC Scopus subject areas

  • Waste Management and Disposal
  • Economics and Econometrics

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