A reinforcement learning approach to solving very-short term train rescheduling problem for a single-track rail corridor

Liu, J., Lin, Z. and Liu, R. (2024) A reinforcement learning approach to solving very-short term train rescheduling problem for a single-track rail corridor. Journal of Rail Transport Planning and Management. 100483. ISSN 2210-9706

Abstract

Metadata

Item Type: Article
Authors/Creators:
  • Liu, J.
  • Lin, Z.
  • Liu, R.
Copyright, Publisher and Additional Information:

© 2024 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License (CC-BY-NC 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.

Keywords: Reinforcement learning; Q learning; Train rescheduling; Single-track; Railway traffic management
Dates:
  • Published: December 2024
  • Published (online): 25 September 2024
  • Accepted: 20 September 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Spatial Modelling and Dynamics (Leeds)
Funding Information:
Funder
Grant number
Rail Safety & Standards Board
Not Known
Depositing User: Symplectic Publications
Date Deposited: 26 Sep 2024 11:19
Last Modified: 26 Sep 2024 11:19
Status: Published
Publisher: Elsevier
Identification Number: 10.1016/j.jrtpm.2024.100483
Open Archives Initiative ID (OAI ID):

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