Multi-objective combinatorial optimization analysis of the recycling of retired new energy electric vehicle power batteries in a sustainable dynamic reverse logistics network.

Mu, Nengye; Wang, Yuanshun; Chen, Zhen-Song; Xin, Peiyuan; Deveci, Muhammet; Pedrycz, Witold

Mu, Nengye; Wang, Yuanshun; Chen, Zhen-Song; Xin, Peiyuan; Deveci, Muhammet; Pedrycz, Witold.

Afiliação

Mu N; School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 611756, Sichuan, China.
Wang Y; College of Transportation Engineering, Xinjiang University, Urumqi, 830046, Xinjiang, China.
Chen ZS; National and Local Joint Engineering Laboratory for Intelligent Integrated Transportation, Chengdu, 611756, Sichuan, China.
Xin P; National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Chengdu, 611756, Sichuan, China.
Deveci M; School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 611756, Sichuan, China.
Pedrycz W; School of Civil Engineering, Wuhan University, Wuhan, 430072, Hubei, China. zschen@whu.edu.cn.

Environ Sci Pollut Res Int ; 30(16): 47580-47601, 2023 Apr.

Article em En | MEDLINE | ID: mdl-36745350

Assuntos

Fontes de Energia Elétrica; Reciclagem; Reciclagem/métodos; Modelos Logísticos

Palavras-chave

Dynamic reverse logistics network; Multi-objective combinatorial optimization; New energy vehicle; Retired power battery; Reverse logistics

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Fontes de Energia Elétrica / Reciclagem Tipo de estudo: Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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