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

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dc.authoridChen, Zhen-Song/0000-0003-4360-5459
dc.authoridWang, Yuanshun/0000-0003-2876-9236
dc.authoridDeveci, Muhammet/0000-0002-3712-976X
dc.authoridMu, Nengye/0000-0002-8140-7501
dc.authorwosidChen, Zhen-Song/K-3436-2019
dc.authorwosidWang, Yuanshun/KFG-0587-2024
dc.authorwosidDeveci, Muhammet/V-8347-2017
dc.contributor.authorMu, Nengye
dc.contributor.authorWang, Yuanshun
dc.contributor.authorChen, Zhen-Song
dc.contributor.authorXin, Peiyuan
dc.contributor.authorDeveci, Muhammet
dc.contributor.authorPedrycz, Witold
dc.date.accessioned2024-05-19T14:46:32Z
dc.date.available2024-05-19T14:46:32Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractThe recycling of retired new energy vehicle power batteries produces economic benefits and promotes the sustainable development of environment and society. However, few attentions have been paid to the design and optimization of sustainable reverse logistics network for the recycling of retired power batteries. To this end, we develop a six-level sustainable dynamic reverse logistics network model from the perspectives of economy, environment, and society. We solve the multi-objective combinatorial optimization model to explore the layout of the sustainable reverse logistics network for retired new energy vehicle power batteries recycling. A case study is implemented to verify the effectiveness of the proposed model. The results show that (a) the facility nodes near the front of the network fluctuate more by opening and closing; (b) the dynamic reverse logistics network is superior to its static counterpart; and (c) cooperation cost changes affect the transaction volume between third-party and cooperative enterprises and total network cost.en_US
dc.identifier.doi10.1007/s11356-023-25573-w
dc.identifier.endpage47601en_US
dc.identifier.issn0944-1344
dc.identifier.issn1614-7499
dc.identifier.issue16en_US
dc.identifier.pmid36745350en_US
dc.identifier.scopus2-s2.0-85147557097en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage47580en_US
dc.identifier.urihttps://doi.org10.1007/s11356-023-25573-w
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5542
dc.identifier.volume30en_US
dc.identifier.wosWOS:000950271400014en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofEnvironmental Science and Pollution Researchen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectRetired Power Batteryen_US
dc.subjectNew Energy Vehicleen_US
dc.subjectReverse Logisticsen_US
dc.subjectMulti-Objective Combinatorial Optimizationen_US
dc.subjectDynamic Reverse Logistics Networken_US
dc.titleMulti-objective combinatorial optimization analysis of the recycling of retired new energy electric vehicle power batteries in a sustainable dynamic reverse logistics networken_US
dc.typeArticleen_US

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