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Last train scheduling for maximizing passenger destination reachability in urban rail transit networks

Author

Listed:
  • Zhou, Yu
  • Wang, Yun
  • Yang, Hai
  • Yan, Xuedong

Abstract

As urban rail transit (URT) systems usually do not operate for the whole day, the last train service offers the last daily chance for late-night passengers to utilize URT services to reach their target destination stations. This paper formally introduces and models the destination-reachability based last train timetabling problem (DR-LTTP in abbreviation) in URT networks, which involves both the last train timetabling and the passenger assignment. The DR-LTTP is formulated as a mixed integer linear programming and can be solved by existing commercial optimization software. The model is illustrated with a simple numerical example on a minimum spanning tree network, and comparison experiments are conducted between DR-LTTP model and station-transferability based last train timetabling problem (ST-LTTP in abbreviation). Finally, a real case study with Beijing URT network is conducted to test the performance of our model.

Suggested Citation

  • Zhou, Yu & Wang, Yun & Yang, Hai & Yan, Xuedong, 2019. "Last train scheduling for maximizing passenger destination reachability in urban rail transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 129(C), pages 79-95.
    • Handle: RePEc:eee:transb:v:129:y:2019:i:c:p:79-95
    DOI: 10.1016/j.trb.2019.09.006
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    Cited by:

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    2. Ning, Jia & Xing, Xinjie & Wang, Yadong & Yao, Yu & Kang, Liujiang & Peng, Qiyuan, 2024. "Coordinating last-train timetabling with app-based ride-hailing service under uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
    3. Mo, Pengli & D’Ariano, Andrea & Yang, Lixing & Veelenturf, Lucas P. & Gao, Ziyou, 2021. "An exact method for the integrated optimization of subway lines operation strategies with asymmetric passenger demand and operating costs," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 283-321.
    4. Luan, Xiaojie & Corman, Francesco, 2022. "Passenger-oriented traffic control for rail networks: An optimization model considering crowding effects on passenger choices and train operations," Transportation Research Part B: Methodological, Elsevier, vol. 158(C), pages 239-272.
    5. Xuan Li & Toshiyuki Yamamoto & Tao Yan & Lili Lu & Xiaofei Ye, 2020. "First Train Timetabling for Urban Rail Transit Networks with Maximum Passenger Transfer Satisfaction," Sustainability, MDPI, vol. 12(10), pages 1-22, May.
    6. Kang, Liujiang & Li, Hao & Sun, Huijun & Wu, Jianjun & Cao, Zhiguang & Buhigiro, Nsabimana, 2021. "First train timetabling and bus service bridging in intermodal bus-and-train transit networks," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 443-462.
    7. Zhang, Di & Gao, Yuan & Yang, Lixing & Cui, Lixin, 2024. "Timetable synchronization of the last several trains at night in an urban rail transit network," European Journal of Operational Research, Elsevier, vol. 313(2), pages 494-512.
    8. Zhang, Quan & Li, Xuan & Yan, Tao & Lu, Lili & Shi, Yang, 2022. "Last train timetabling optimization for minimizing passenger transfer failures in urban rail transit networks: A time period based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).

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