2026-07-27T19:49:50Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:19083 2024-03-06T11:03:28Z ddc:004 open_access

Constraint Programming to Improve Hub Utilization in Autonomous Transfer Hub Networks (Short Paper) Lee, Chungjae Boonbandansook, Wirattawut Akhlaghi, Vahid Eghbal Dalmeijer, Kevin Van Hentenryck, Pascal Constraint Programming Autonomous Trucking Tranfer Hub Network The Autonomous Transfer Hub Network (ATHN) is one of the most promising ways to adapt self-driving trucks for the freight industry. These networks use autonomous trucks for the middle mile, while human drivers perform the first and last miles. This paper extends previous work on optimizing ATHN operations by including transfer hub capacities, which are crucial for labor planning and policy design. It presents a Constraint Programming (CP) model that shifts an initial schedule produced by a Mixed Integer Program to minimize the hub capacities. The scalability of the CP model is demonstrated on a case study at the scale of the United States, based on data provided by Ryder System, Inc. The CP model efficiently finds optimal solutions and lowers the necessary total hub capacity by 42%, saving $15.2M in annual labor costs. The results also show that the reduced capacity is close to a theoretical (optimistic) lower bound. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Chungjae Lee and Wirattawut Boonbandansook and Vahid Eghbal Akhlaghi and Kevin Dalmeijer and Pascal Van Hentenryck 2023 Is Part Of LIPIcs, Volume 280, 29th International Conference on Principles and Practice of Constraint Programming (CP 2023) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.CP.2023.46 urn:nbn:de:0030-drops-190835 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2023.46 eng https://creativecommons.org/licenses/by/4.0/legalcode