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Timetable Rescheduling Using Skip-Stop Strategy for Sustainable Urban Rail Transit

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  • Zhichao Cao

    (School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China
    Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province, Chengdu 610041, China
    Guangdong-Hong Kong-Macau Joint Laboratory for Smart Cities, Shenzhen 518100, China)

  • Yuqing Wang

    (School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China)

  • Zihao Yang

    (School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China)

  • Changjun Chen

    (School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China)

  • Silin Zhang

    (School of Transportation and Civil Engineering, Nantong University, Nantong 226019, China)

Abstract

Unanticipated events inevitably occur in daily urban rail transit operations, disturbing the scheduled timetable. Despite the mild delay, the busy operation system probably tends to worsen a larger disturbance and even lead to a knock-on disruption if no rescheduling is timely carried out. We propose a bi-objective mixed-integer linear programming model (MILP) that employs the skip-stop operation strategy to eliminate unscheduled delays. This model addresses two distinct, yet interconnected objectives. Firstly, it aims to minimize the difference between the plan and the actual operation. Secondly, it strives to minimize the number of left-behind passengers. In order to resolve this MILP problem, we devised a Pareto-based genetic algorithm (GA). Based on the case study, we certify the superior effectiveness with comparisons to the whale optimization algorithm and the epsilon constraint method. The outcomes affirm that our model has the potential to reduce the total delay time of the line by 44.52% at most compared with the traditional all-stop running adjustment model. The optimal scheme saved 6.08% of the total costs based on a trade-off between operators’ interests and passenger satisfaction.

Suggested Citation

  • Zhichao Cao & Yuqing Wang & Zihao Yang & Changjun Chen & Silin Zhang, 2023. "Timetable Rescheduling Using Skip-Stop Strategy for Sustainable Urban Rail Transit," Sustainability, MDPI, vol. 15(19), pages 1-29, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:19:p:14511-:d:1254163
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    References listed on IDEAS

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    1. Han, Zhenyu & Han, Baoming & Li, Dewei & Ning, Shangbin & Yang, Ruixia & Yin, Yonghao, 2021. "Train timetabling in rail transit network under uncertain and dynamic demand using Advanced and Adaptive NSGA-II," Transportation Research Part B: Methodological, Elsevier, vol. 154(C), pages 65-99.
    2. Li, Shukai & Dessouky, Maged M. & Yang, Lixing & Gao, Ziyou, 2017. "Joint optimal train regulation and passenger flow control strategy for high-frequency metro lines," Transportation Research Part B: Methodological, Elsevier, vol. 99(C), pages 113-137.
    3. 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.
    4. 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.
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    Cited by:

    1. Yunfang Ma & Jose M. Sallan & Oriol Lordan, 2024. "Rail Transit Networks and Network Motifs: A Review and Research Agenda," Sustainability, MDPI, vol. 16(9), pages 1-21, April.

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