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Timetable Design for Urban Rail Line with Capacity Constraints

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  • Yu-Ting Zhu
  • Bao-Hua Mao
  • Lu Liu
  • Ming-Gao Li

Abstract

To design an efficient and economical timetable for a heavily congested urban rail corridor, a scheduling model is proposed in this paper. The objective of the proposed model is to find the departure time of trains at the start terminal to minimize the system cost, which includes passenger waiting cost and operating cost. To evaluate the performance of the timetable, a simulation model is developed to simulate the detailed movements of passengers and trains with strict constraints of station and train capacities. It assumes that passengers who arrive early will have more chances to access a station and board a train. The accessing and boarding processes of passengers are all based on a first-come-first-serve basis. When a station is full, passengers unable to access must wait outside until the number of waiting passengers at platform falls below a given value. When a train is full, passengers unable to board must wait at the platform for the next train to arrive. Then, based on the simulation results, a two-stage genetic algorithm is introduced to find the best timetable. Finally, a numerical example is given to demonstrate the effectiveness of the proposed model and solution method.

Suggested Citation

  • Yu-Ting Zhu & Bao-Hua Mao & Lu Liu & Ming-Gao Li, 2015. "Timetable Design for Urban Rail Line with Capacity Constraints," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-11, August.
  • Handle: RePEc:hin:jnddns:429219
    DOI: 10.1155/2015/429219
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    Cited by:

    1. Shi, Jungang & Yang, Jing & Yang, Lixing & Tao, Lefeng & Qiang, Shengjie & Di, Zhen & Guo, Junhua, 2023. "Safety-oriented train timetabling and stop planning with time-varying and elastic demand on overcrowded commuter metro lines," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    2. Erfan Hassannayebi & Seyed Hessameddin Zegordi & Mohammad Reza Amin-Naseri & Masoud Yaghini, 2018. "Optimizing headways for urban rail transit services using adaptive particle swarm algorithms," Public Transport, Springer, vol. 10(1), pages 23-62, May.

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