Integrated optimization of rolling stock allocation and train timetables for urban rail transit networks: A benders decomposition approach

The authors investigate the integrated optimization of rolling stock allocation and train timetables (RATT) in an urban rail transit network with multiple connected lines and rolling stock depots. Different from most existing research on single-line cases, the authors consider that the rail manager plans to allocate a certain fleet of rolling stock to depots to implement the operational timetables of multiple lines, where each depot can serve more than one line but has limited capacity. By means of the construction of a space–time network, the authors formulate RATT into a bi-objective mixed-integer linear programming (MILP) model. The model can simultaneously generate the rolling stock allocation plan and train schedules for the considered lines, with the aim of optimizing both the investment cost of rolling stock and the service quality of passengers. Due to the computational complexity of large-scale real-world instances, the authors develop a Benders decomposition-based solution algorithm, which decomposes the MILP into a rolling stock assignment problem and a set of independent subproblems, i.e., a train scheduling subproblem for each line. As the subproblems also contain integral variables, the authors further prove that a large portion of the subproblems, after proper reformulation, has the integrality property and can be solved rapidly via linear relaxation. The authors test their integrated approach and solution algorithms on real-world instances from the Beijing rail transit network. The results show that the authors' solution approach can obtain near optimal solutions, while the commercial solvers cannot even return feasible solutions on real-world instances. Compared to the existing plan in the Beijing metro, the authors' RATT approach can improve the service quality by 17.6%, on average, using the same fleet size of rolling stock.

• Record URL:
  • https://doi.org/10.1016/j.trb.2023.102815
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0191261523001406
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01912615
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Yin, Jiateng
  • Pu, Fan
  • Yang, Lixing
  • 0000-0003-1628-5015
  • D’Ariano, Andrea
  • Wang, Zhouhong
• Publication Date: 2023-10

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References;
• Pagination: 102815
• Serial:
  • Transportation Research Part B: Methodological
  • Volume: 176
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0191-2615
  • Serial URL: http://www.sciencedirect.com/science/journal/01912615

Subject/Index Terms

• TRT Terms: Fleet management; Optimization; Rail transit; Rolling stock; Timetables; Urban transit
• Geographic Terms: Beijing (China)
• Subject Areas: Operations and Traffic Management; Railroads; Vehicles and Equipment;

Filing Info

• Accession Number: 01892511
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 8 2023 4:35PM