Scheduling Electric Buses with Stochastic Driving Times

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

To try to make the world more sustainable and reduce air pollution, diesel buses are being replaced with electric buses. This leads to challenges in scheduling, as electric buses need recharging during the day. Moreover, buses encounter varying traffic conditions and passenger demands, leading to delays. Scheduling electric buses with these stochastic driving times is also called the Stochastic Vehicle Scheduling Problem. The classical approach to make a schedule more robust against these delays, is to add slack to the driving time. However, this approach doesn't capture the variance of a distribution well, and it doesn't account for dependencies between trips. We use discrete event simulation in order to evaluate the robustness of a schedule. Then, to create a schedule, we use a hybrid approach, where we combine integer linear programming and simulated annealing with the use of these simulations. We show that with the use of our hybrid algorithm, the punctuality of the buses increase, and they also have a more timely arrival. However, we also see a slight increase in operating cost, as we need slightly more buses compared to when we use deterministic driving times.
Original languageEnglish
Title of host publication23rd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2023)
EditorsDaniele Frigioni, Philine Schiewe
Place of PublicationDagstuhl, Germany
PublisherSchloss Dagstuhl -- Leibniz-Zentrum für Informatik
Pages14:1-14:19
Number of pages19
ISBN (Electronic)978-3-95977-302-7
ISBN (Print)978-3-95977-302-7
DOIs
Publication statusPublished - Sept 2023
Event23rd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2023) - CWI, Amsterdam, Netherlands
Duration: 7 Sept 20238 Sept 2023
https://algo-conference.org/2023/atmos/

Publication series

NameOpenAccess Series in Informatics
Volume115
ISSN (Print)2190-6807

Conference

Conference23rd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2023)
Abbreviated titleATMOS 2023
Country/TerritoryNetherlands
CityAmsterdam
Period7/09/238/09/23
Internet address

Bibliographical note

Publisher Copyright:
© 2023 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

Keywords

  • Electric Vehicle Scheduling Problem
  • Simulated Annealing
  • Hybrid Algorithm
  • Simulation
  • Stochastic Driving Times

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