School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, 611756, Sichuan, China.
College of Transportation Engineering, Xinjiang University, Urumqi, 830046, Xinjiang, China.
Environ Sci Pollut Res Int. 2023 Apr;30(16):47580-47601. doi: 10.1007/s11356-023-25573-w. Epub 2023 Feb 6.
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.
退役新能源汽车动力蓄电池的回收利用可以产生经济效益，促进环境和社会的可持续发展。然而，对于退役动力电池回收的可持续逆向物流网络的设计和优化，关注较少。为此，我们从经济、环境和社会的角度出发，构建了一个六级可持续动态逆向物流网络模型。通过求解多目标组合优化模型，探讨了退役新能源汽车动力蓄电池回收的可持续逆向物流网络布局。通过案例研究验证了所提模型的有效性。结果表明：（a）靠近网络前端的设施节点在开闭时波动更大；（b）动态逆向物流网络优于静态网络；（c）合作成本变化会影响第三方和合作企业之间的交易量和总网络成本。
