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.
@article{arxiv.2201.06137,
title = {Optimization Models for Autonomous Transfer Hub Networks},
author = {Chungjae Lee and Kevin Dalmeijer and Pascal Van Hentenryck},
journal= {arXiv preprint arXiv:2201.06137},
year = {2022}
}
Comments
8 pages, 7 figures, 2 tables. arXiv admin note: text overlap with arXiv:2110.12327