Paper
21 July 2024 Modeling the train manning problem for a massive rapid transit line
Defang Wang, Xinpeng Li, Yuhao Zheng, Xiaoning Zhu, Liujiang Kang
Author Affiliations +
Proceedings Volume 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024); 132193V (2024) https://doi.org/10.1117/12.3036901
Event: 4th International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2024), 2024, Kaifeng, China
Abstract
This study proposes a practical train manning problem (TMP) for a bi-directional massive rapid transit (MRT) line with a certain number of crew points. The TMP aims to determine a set of manning duties for each rover to man the daily train services subjected to practical constraints by minimizing the total idle time of rovers. It is crucial for the MRT operators to solve the TMP because rovers are able to handle possible train faults and/or emergencies through their fast responses. In this paper, we build a binary nonlinear and nonconvex programming model with explicit constraints for the proposed TMP, by considering three possible train manning scenarios with different idle times. Moreover, we conduct a case study of the Singapore circle line and perform necessary sensitivity analysis of various parameters involved in the TMP. Results indicate that our model can solve the TMP problem effectively and the solutions help to improve the manning duties assignment.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Defang Wang, Xinpeng Li, Yuhao Zheng, Xiaoning Zhu, and Liujiang Kang "Modeling the train manning problem for a massive rapid transit line", Proc. SPIE 13219, Fourth International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2024), 132193V (21 July 2024); https://doi.org/10.1117/12.3036901
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KEYWORDS
Education and training

Autonomous driving

Binary data

Mathematical optimization

Computer programming

Modeling

Reliability

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