Peak Hour Stopping Scheme Optimization of Suburban Line Considering Train Capacity Constraints

The passenger flow of suburban rail transit lines in metropolises often have long travel distance and uneven temporal and spatial distributions. Especially during peak hours, there are stranded passengers on the platform due to limited train capacities. Train operations with differentiated stopping scheme is an effective way to improve the peak hour operations. This paper proposes an optimization model that minimizes the total passenger travel cost including waiting time and travel time based on the calculation of boarding/alighting, transferring/arriving, and remaining onboard passenger numbers. With the uniform encoding of 0-1 variables that indicate whether trains stop at a station, an improved genetic algorithm with catastrophe theory is developed by setting the maximum number of catastrophes triggered. The mean deviation and deviation range of the departure intervals between subsequent trains at stations are used as the indicators to evaluate the equilibrium of the timetable, and the train stopping patterns are then optimized in consideration of the train capacities. The case study in Beijing Subway Line 15 shows that the improved genetic algorithm can effectively escape from local optima through catastrophe operations. The algorithm can obtain the optimal stopping scheme under three designed scenarios, particularly, the objective value of scenarios 2 and 3 was respectively improved by 12.20% and 4.28% compared to scenario 1. The skip-stop strategy can effectively reduce the train's running time, for example, the train running time in scenarios 2 and 3 was respectively saved by 17.49 s and 17.97 s in the downstream direction compared to scenario 1. © 2023 Science Press. All rights reserved.