电池(电)
运筹学
布线(电子设计自动化)
计算机科学
钥匙(锁)
分布(数学)
线性规划
总成本
业务
环境经济学
计算机网络
工程类
计算机安全
经济
数学
量子力学
物理
会计
数学分析
功率(物理)
算法
作者
Junxia Zhang,Xingmei Li,Dongqing Jia,Yuexin Zhou
出处
期刊:Energy
[Elsevier]
日期:2023-03-09
卷期号:272: 127152-127152
被引量:9
标识
DOI:10.1016/j.energy.2023.127152
摘要
In logistics field, considering high cost of self-built battery swapping stations and limited public battery swapping, some investors start to establish union battery swapping stations for logistics companies, which has received positive response. In this case, station location and logistics distribution routes are key decisions, which determine investors' and logistics companies' interests. But meanwhile, the mutual influence between location and routes brings difficulty to decision. However, there is no specific research on this issue. Therefore, based on Bi-level programming, this paper firstly proposes a location-routing decision scheme that considers the mutual influence, and genetic algorithm and linear technology are combined to solve it. Moreover, to ensure each logistics company's interest, this paper proposes to introduce joint distribution among logistics companies and use Shapley value to allocate total cost. And by the comparison of three different scenarios, the study finds, Bi-level programming can solve location-routing problem, and make logistics companies spend less cost than self-built method. Further, when logistics group carry out joint distribution, the total distribution cost can fall by 4%, and correspondingly, allocation strategy can reduce each logistics company’ cost. Meanwhile, the benefits of the investor of the union battery swapping station will also increase by 4%.
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