论文标题
自主转移集线器网络的优化模型
Optimization Models for Autonomous Transfer Hub Networks
论文作者
论文摘要
预计自动驾驶卡车将从根本上改变货运行业。特别是，将自动驾驶汽车与中部里程与人类驱动的第一和最后一英里相结合的自主转移集线器网络（ATHN）被视为该技术最有可能的部署途径。本文提出了三种优化ATHN操作并进行比较的方法：一个约束编程模型，一种列生成方法和定制网络流量方法。实际案例研究的结果表明，网络流量模型是高度可扩展的，并以显着的边距优于其他两种方法。
Autonomous trucks are expected to fundamentally transform the freight transportation industry. In particular, Autonomous Transfer Hub Networks (ATHN), which combine autonomous trucks on middle miles with human-driven on the first and last miles, are seen as the most likely deployment pathway of this technology. This paper presents three methods to optimize ATHN operations and compares them: a constraint-programming model, a column-generation approach, and a bespoke network flow method. Results on a real case study indicate that the network flow model is highly scalable and outperforms the other two approaches by significant margins.
