Estimating the robustness of public transport schedules using machine learning-Reference-Cited by-同舟云学术

Estimating the robustness of public transport schedules using machine learning

Published:2022-04 Issue: Volume:137 Page:103566
ISSN:0968-090X
Container-title:Transportation Research Part C: Emerging Technologies
language:en
Short-container-title:Transportation Research Part C: Emerging Technologies

Author:

Müller-Hannemann Matthias,Rückert Ralf^ORCID,Schiewe Alexander^ORCID,Schöbel Anita^ORCID

Funder

Deutsche Forschungsgemeinschaft

Publisher

Elsevier BV

Subject

Management Science and Operations Research,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference74 articles.

1. Quantifying railway timetable robustness in critical points;Andersson;J. Rail Transp. Plan. Manag.,2013

2. Route planning in transportation networks;Bast,2016

3. Rules of thumb — practical online strategies for delay management;Bauer;Public Transp.,2014

4. Borndörfer, R., Karbstein, M., Liebchen, C., Lindner, N., 2018. A simple way to compute the number of vehicles that are required to operate a periodic timetable.In: R. Borndörfer and S. Storandt (Ed.), 18th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2018). volume 65 of OpenAccess Series in Informatics (OASIcs). 16:1–16:15. Schloss Dagstuhl–Leibniz-Zentrum für Informatik. https://doi.org/10.4230/OASIcs.ATMOS.2018.16.

5. Handbook of Optimization in the Railway Industry, Volume 268;Borndörfer,2018

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