Optimization of Multi-Day Flexible EMU Routing Plan for High-Speed Rail Networks
Source abstract
Abstract
With the continuous expansion and increasing operational complexity of high-speed railway networks, there is a growing need for more flexible and efficient EMU (Electric Multiple Unit) routing strategies. To address these challenges, in this paper, we propose a multi-day flexible circulation model that minimizes total connection time and deadheading mileage. A multi-commodity network flow model is formulated, incorporating constraints such as first-level maintenance intervals, storage capacity, train coupling/decoupling operations, and train types, with across-day consistency. To solve this complex model efficiently, a heuristic decomposition algorithm is designed to separate the problem into daily service chain generation and EMU assignment. A real-world case study in the Beijing–Baotou high-speed corridor demonstrates the effectiveness of the proposed approach. Compared to a fixed strategy, the flexible strategy reduces EMU usage by one unit, lowers deadheading mileage by up to 16.4%, and improves maintenance workload balance. These results highlight the practical value of flexible EMU deployment for large-scale, multi-day railway operations.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Railway Systems and Energy Efficiency · Transportation Systems and Safety · Transport and Economic Policies
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Funding
China State Railway Group Co., Ltd. · Research Project of China Railway Beijing Group Co., Ltd.
References (27)
Show source-provided references
1. The fuxing: The China standard EMU10.1016/j.eng.2020.01.004 ↗
2. The integrated rolling stock circulation and depot location problem in railway rapid transit systems10.1016/j.tre.2017.10.018 ↗
3. A Lagrangian heuristic for a train-unit assignment problem10.1016/j.dam.2011.10.035 ↗
4. A pragmatic algorithm for the train-set routing: The case of Korea high-speed railway10.1016/j.omega.2008.03.003 ↗
5. A comparison of two exact methods for passenger railway rolling stock (re)scheduling10.1016/j.tre.2016.03.019 ↗
6. Optimization models for high-speed train unit routing problems10.1016/j.cie.2018.02.039 ↗
7. Optimization of the electric multiple units circulation plan with the minimum number of train-set
8. Maróti, G., and Kroon, L.G. (2004). Maintenance routing for train units: The scenario model. CWI, Probability, Networks and Algorithms (PNA), CWI.
9. Maintenance routing for train units: The transition model10.1287/trsc.1050.0116 ↗
10. Maintenance routing for train units: The interchange model10.1016/j.cor.2005.05.026 ↗
11. A rolling stock circulation model for railway rapid transit systems10.1016/j.trpro.2014.10.047 ↗
12. A combined column generation and heuristics for railway short-term rolling stock planning with regular inspection constraints10.1016/j.cor.2016.11.025 ↗
13. Integrated optimization of rolling stock rotations for intercity railways10.1287/trsc.2015.0633 ↗
14. A branch-and-price algorithm for railway rolling stock rescheduling10.1016/j.trb.2017.03.003 ↗
15. Rolling stock scheduling with maintenance requirements at the Chinese High-Speed Railway10.1016/j.trb.2019.05.013 ↗
16. Optimization method for railway rolling stock planning considering parking conditions
17. Strength of energy consumption cost for EMU based on flexible train formation
18. A rolling stock circulation model for combining and splitting of passenger trains10.1016/j.ejor.2005.03.032 ↗
19. Circulation of railway rolling stock: A branch-and-price approach10.1016/j.cor.2006.03.019 ↗
20. Improving robustness of rolling stock circulations in rapid transit networks10.1016/j.cor.2014.05.007 ↗
21. A branch-and-price approach for trip sequence planning of high-speed train units10.1016/j.omega.2019.102150 ↗
22. Research on optimization of flexible train composition circulation plan considering passenger demand
23. Integrated optimization of train formation plan and rolling stock scheduling under time-dependent demand10.1016/j.cor.2022.106049 ↗
24. Optimization of urban rail rolling stock scheduling under coupling train formation
25. Urban rail rolling stock scheduling with flexible train formations and robust passenger flow control strategy
26. Passenger-oriented rolling stock scheduling in the metro system with multiple depots: Network flow based approaches10.1016/j.trb.2024.102885 ↗
27. Gurobi Optimization, LLC (2021, August 04). Gurobi Optimizer Reference Manual. Available online: https://www.gurobi.com.