Re-Scheduling of Urban Rail Trains Based on Stop-Skip Pattern in Passenger Traffic Congestion

Today, urban railroads play a key role in the public transport of large cities, as this type of transportation system has a higher transport capacity and efficiency compared to other conventional public transportation modes. In this research, a two-objective optimization model is presented by integrating the re-scheduling approach and the stop-skip pattern in passenger traffic conditions after the end of the disruption. This model simulates the flow of passengers according to the timetable based on the time-dependent arrival time of the passengers. Due to the complexity of the re-scheduling problem, a decomposition algorithm was presented for producing near-optimal solutions. Validation of the
re-scheduling model was carried out using numerical tests based on operational data from Tehran and Beijing railways. Based on the results of the re-scheduling model, by increasing the total travel time of trains by less than 1%, the passenger overcrowding in line 5 of Tehran's urban railway could be reduced by about 35%. Regarding the need for a fast response after disruption, the re-scheduling algorithm is efficient. Experimental results show that even in large-scale test problems, the solution approach has a good quality response and computational time, which indicates its effectiveness in re-planning the trains of urban railways.