2026-08-04T19:28:24Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:21199 2024-10-07T04:59:11Z ddc:004 open_access

Solving the Electric Bus Scheduling Problem by an Integrated Flow and Set Partitioning Approach Borndörfer, Ralf Löbel, Andreas Löbel, Fabian Weider, Steffen Electric Bus Scheduling Electric Vehicle Scheduling Non-linear Charging Multi-commodity Flow Set Partition Lagrangian Relaxation Proximal Bundle Method Attractive and cost-efficient public transport requires solving computationally difficult optimization problems from network design to crew rostering. While great progress has been made in many areas, new requirements to handle increasingly complex constraints are constantly coming up. One such challenge is a new type of resource constraints that are used to deal with the state-of-charge of battery-electric vehicles, which have limited driving ranges and need to be recharged in-service. Resource constrained vehicle scheduling problems can classically be modelled in terms of either a resource constrained (multi-commodity) flow problem or in terms of a path-based set partition problem. We demonstrate how a novel integrated version of both formulations can be leveraged to solve resource constrained vehicle scheduling with replenishment in general and the electric bus scheduling problem in particular by Lagrangian relaxation and the proximal bundle method. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Ralf Borndörfer and Andreas Löbel and Fabian Löbel and Steffen Weider 2024 Is Part Of OASIcs, Volume 123, 24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2024) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.ATMOS.2024.11 urn:nbn:de:0030-drops-211992 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2024.11 eng https://creativecommons.org/licenses/by/4.0/legalcode