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Solving the Electric Bus Scheduling Problem by an Integrated Flow and Set Partitioning Approach

Authors Ralf Borndörfer , Andreas Löbel, Fabian Löbel , Steffen Weider

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Subject Classification

ACM Subject Classification
  • Mathematics of computing → Mathematical optimization
  • Mathematics of computing → Network flows
  • Mathematics of computing → Integer programming
  • Mathematics of computing → Linear programming
  • Applied computing → Transportation
Keywords
  • Electric Bus Scheduling
  • Electric Vehicle Scheduling
  • Non-linear Charging
  • Multi-commodity Flow
  • Set Partition
  • Lagrangian Relaxation
  • Proximal Bundle Method

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Abstract

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.

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Ralf Borndörfer, Andreas Löbel, Fabian Löbel, and Steffen Weider. Solving the Electric Bus Scheduling Problem by an Integrated Flow and Set Partitioning Approach. In 24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2024). Open Access Series in Informatics (OASIcs), Volume 123, pp. 11:1-11:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/OASIcs.ATMOS.2024.11

Author Details

Ralf Borndörfer
  • Zuse Institute Berlin, Germany
Andreas Löbel
  • IVU Traffic Technologies AG, Berlin, Germany
Fabian Löbel
  • Zuse Institute Berlin, Germany
Steffen Weider
  • IVU Traffic Technologies AG, Berlin, Germany

Funding

This work has been conducted within the Research Campus MODAL funded by the German Federal Ministry of Education and Research (BMBF) (fund number 05M20ZBM).

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