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

The 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 powe...

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Vydané v:Environmental science and pollution research international Ročník 30; číslo 16; s. 47580 - 47601
Hlavní autori: Mu, Nengye, Wang, Yuanshun, Chen, Zhen-Song, Xin, Peiyuan, Deveci, Muhammet, Pedrycz, Witold
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2023
Springer Nature B.V
Predmet:
Alliances
Aquatic Pollution
Atmospheric Protection/Air Quality Control/Air Pollution
case studies
Combinatorial analysis
Design optimization
Earth and Environmental Science
Ecotoxicology
Electric Power Supplies
Electric vehicles
energy
Environment
Environmental Chemistry
Environmental Health
Environmental science
Logistic Models
Multiple objective analysis
Optimization
Optimization models
Recycling
Recycling - methods
Research Article
Reverse logistics
society
Sustainability
Sustainable development
Waste Water Technology
Water Management
Water Pollution Control
New energy vehicle
Dynamic reverse logistics network
Retired power battery
Reverse logistics
Multi-objective combinatorial optimization
ISSN:1614-7499, 0944-1344, 1614-7499
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Popis
Shrnutí:The 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.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1614-7499
0944-1344
1614-7499
DOI:10.1007/s11356-023-25573-w