Dynamic scheduling of flexible bus services with hybrid requests and fairness: Heuristics-guided multi-agent reinforcement learning with imitation learning

Wu, W., Zhu, Y. and Liu, R. orcid.org/0000-0003-0627-3184 (2024) Dynamic scheduling of flexible bus services with hybrid requests and fairness: Heuristics-guided multi-agent reinforcement learning with imitation learning. Transportation Research Part B: Methodological, 190. 103069. ISSN 0191-2615

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Item Type: Article
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© 2024, Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. This is an author produced version of an article published in Transportation Research Part B: Methodological. Uploaded in accordance with the publisher's self-archiving policy.

Keywords: Flexible bus, Multi-agent reinforcement learning Imitation learning, Local search, Demand prediction
Dates:
  • Published: 1 December 2024
  • Published (online): 18 September 2024
  • Accepted: 29 August 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)
Depositing User: Symplectic Publications
Date Deposited: 23 Oct 2024 14:48
Last Modified: 23 Oct 2024 14:49
Published Version: https://www.sciencedirect.com/science/article/pii/...
Status: Published
Publisher: Elsevier
Identification Number: 10.1016/j.trb.2024.103069
Open Archives Initiative ID (OAI ID):

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Filename: DRT-RL-accept - Sept2024.pdf

Licence: CC-BY-NC-ND 4.0

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