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Service-oriented train timetabling with collaborative passenger flow control on an oversaturated metro line: An integer linear optimization approach

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  • Shi, Jungang
  • Yang, Lixing
  • Yang, Jing
  • Gao, Ziyou

Abstract

With the drastic increase of travel demands in urban areas, more and more metro lines are nowadays suffering from oversaturated situations, leading to the accumulation of passengers on platforms with potential accident risks. To further improve the service quality and reduce accident risks, this paper proposes an effective method for collaboratively optimizing the train timetable and accurate passenger flow control strategies on an oversaturated metro line. Through considering the dynamic characteristics of passenger flow, a rigorous integrated integer linear programming model is firstly formulated to minimize the total passenger waiting time at all of involved stations, in which the train timetable provides a service-oriented operation plan and optimal passenger flow control is imposed to avoid congestion on platforms within the transportation capacities. To solve the problem of interest efficiently, a hybrid algorithm, which combines an improved local search and CPLEX solver, is designed to search for high-quality solutions. Finally, two sets of numerical experiments, including a small-scale case and a real-world instance with operation data of the Beijing metro system, are implemented to demonstrate the performance and effectiveness of the proposed approaches.

Suggested Citation

  • Shi, Jungang & Yang, Lixing & Yang, Jing & Gao, Ziyou, 2018. "Service-oriented train timetabling with collaborative passenger flow control on an oversaturated metro line: An integer linear optimization approach," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 26-59.
    • Handle: RePEc:eee:transb:v:110:y:2018:i:c:p:26-59
    DOI: 10.1016/j.trb.2018.02.003
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    1. Cepeda, M. & Cominetti, R. & Florian, M., 2006. "A frequency-based assignment model for congested transit networks with strict capacity constraints: characterization and computation of equilibria," Transportation Research Part B: Methodological, Elsevier, vol. 40(6), pages 437-459, July.
    2. Niu, Huimin & Zhou, Xuesong & Gao, Ruhu, 2015. "Train scheduling for minimizing passenger waiting time with time-dependent demand and skip-stop patterns: Nonlinear integer programming models with linear constraints," Transportation Research Part B: Methodological, Elsevier, vol. 76(C), pages 117-135.
    3. Gao, Yuan & Kroon, Leo & Schmidt, Marie & Yang, Lixing, 2016. "Rescheduling a metro line in an over-crowded situation after disruptions," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 425-449.
    4. Corman, Francesco & D’Ariano, Andrea & Marra, Alessio D. & Pacciarelli, Dario & Samà, Marcella, 2017. "Integrating train scheduling and delay management in real-time railway traffic control," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 105(C), pages 213-239.
    5. Cacchiani, Valentina & Toth, Paolo, 2012. "Nominal and robust train timetabling problems," European Journal of Operational Research, Elsevier, vol. 219(3), pages 727-737.
    6. Cacchiani, Valentina & Furini, Fabio & Kidd, Martin Philip, 2016. "Approaches to a real-world Train Timetabling Problem in a railway node," Omega, Elsevier, vol. 58(C), pages 97-110.
    7. Christian Liebchen, 2008. "The First Optimized Railway Timetable in Practice," Transportation Science, INFORMS, vol. 42(4), pages 420-435, November.
    8. Yin, Jiateng & Tang, Tao & Yang, Lixing & Gao, Ziyou & Ran, Bin, 2016. "Energy-efficient metro train rescheduling with uncertain time-variant passenger demands: An approximate dynamic programming approach," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 178-210.
    9. Alberto Caprara & Matteo Fischetti & Paolo Toth, 2002. "Modeling and Solving the Train Timetabling Problem," Operations Research, INFORMS, vol. 50(5), pages 851-861, October.
    10. Barrena, Eva & Canca, David & Coelho, Leandro C. & Laporte, Gilbert, 2014. "Single-line rail rapid transit timetabling under dynamic passenger demand," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 134-150.
    11. Zhou, Xuesong & Zhong, Ming, 2007. "Single-track train timetabling with guaranteed optimality: Branch-and-bound algorithms with enhanced lower bounds," Transportation Research Part B: Methodological, Elsevier, vol. 41(3), pages 320-341, March.
    12. Carey, Malachy, 1994. "A model and strategy for train pathing with choice of lines, platforms, and routes," Transportation Research Part B: Methodological, Elsevier, vol. 28(5), pages 333-353, October.
    13. Quattrone, Agata & Vitetta, Antonino, 2011. "Random and fuzzy utility models for road route choice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 1126-1139.
    14. Xu, Xin-yue & Liu, Jun & Li, Hai-ying & Jiang, Man, 2016. "Capacity-oriented passenger flow control under uncertain demand: Algorithm development and real-world case study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 87(C), pages 130-148.
    15. Jiang, Feng & Cacchiani, Valentina & Toth, Paolo, 2017. "Train timetabling by skip-stop planning in highly congested lines," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 149-174.
    16. Zhou, Leishan & Tong, Lu (Carol) & Chen, Junhua & Tang, Jinjin & Zhou, Xuesong, 2017. "Joint optimization of high-speed train timetables and speed profiles: A unified modeling approach using space-time-speed grid networks," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 157-181.
    17. Fernández, Rodrigo & Valencia, Alejandra & Seriani, Sebastian, 2015. "On passenger saturation flow in public transport doors," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 102-112.
    18. Yang, Lixing & Qi, Jianguo & Li, Shukai & Gao, Yuan, 2016. "Collaborative optimization for train scheduling and train stop planning on high-speed railways," Omega, Elsevier, vol. 64(C), pages 57-76.
    19. Yin, Jiateng & Yang, Lixing & Tang, Tao & Gao, Ziyou & Ran, Bin, 2017. "Dynamic passenger demand oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches," Transportation Research Part B: Methodological, Elsevier, vol. 97(C), pages 182-213.
    20. Vansteenwegen, P. & Oudheusden, D. Van, 2006. "Developing railway timetables which guarantee a better service," European Journal of Operational Research, Elsevier, vol. 173(1), pages 337-350, August.
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