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
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.