Due to the high frequency of departures, Urban Rail Transit (URT) has emerged as the top choice for transportation among numerous individuals. However, when there is a disruption, the shorter departure interval poses a huge challenge to train rescheduling. Disruption may cause large-scale train delays or even paralysis of the entire line operation, seriously affecting the travel of passengers. This paper conducts a thorough study on the train rescheduling problem during disruption in URT systems. We implement holding and short-turning strategies and propose a NIP model aimed at minimizing passenger travel costs and deviations from the original train timetable, with the objective of obtaining a better train rescheduling timetable in a short time. We propose an iterative optimization algorithm utilizing Adaptive Large Neighborhood Search (ALNS), and we perform a case study using operational data from the Chengdu metro to validate the efficacy of the train rescheduling timetable. The result indicates that our approach decreases passenger travel costs by 15.50% and reduces timetable deviations by 16.47% when compared to the initial train timetable.


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    Title :

    A Train Rescheduling Approach Under Disruptions in Urban Rail Transit Systems


    Additional title:

    Smart Innovation, Systems and Technologies


    Contributors:
    Wu, Tsu-Yang (editor) / Ni, Shaoquan (editor) / Pan, Jeng-Shyang (editor) / Chu, Shu-Chuan (editor) / Qiu, Peng (author) / Ye, Xuze (author) / Li, Yongxin (author) / Chen, Tao (author)

    Conference:

    International Conference on Smart Vehicular Technology, Transportation, Communication and Applications ; 2024 ; Kaohsiung City, Taiwan April 16, 2024 - April 18, 2024



    Publication date :

    2025-06-22


    Size :

    20 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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