A general metro timetable rescheduling approach for the minimisation of the capacity loss after random line disruption

Shuang Zhang, Yanqiu Cheng, Kuanmin Chen, Chen Ma, Jie Wei, Xianbiao Hu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This study proposes a generic metro timetable rescheduling method for the minimization of the capacity loss that integrates spatial and temporal information on random line disruptions and time-varying characteristics of passenger flows. The proposed emergency operating rules can be immediately deployed after a random disruption using one crossover track. The spatiotemporal information of a disruption and the current state of the line are integrated into a metro disruption management (MDM) model, which considers deviated from the original schedule and the number of stranded passengers as optimization objectives. An iterative meta-heuristic for the general metro rescheduling (IMH-GMR) algorithm is developed to flexibly classify an accident and determine rescheduling solutions for the MDM model within an effective running time (e.g., 15-60 sec). Test results show that the line capacity loss is significantly reduced (94.95%) compared with the total loss caused by the accident disposal in the test scenario.

Original languageEnglish (US)
JournalTransportmetrica A: Transport Science
DOIs
StateAccepted/In press - 2023

All Science Journal Classification (ASJC) codes

  • Transportation
  • General Engineering

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