Timetable Synchronization and Optimization Considering Time-Dependent Passenger Demand in an Urban Subway Network

Abstract

In an urban subway network, a synchronized and optimized timetable can provide a good service to all passengers. Therefore, the timetable is typically the most important factor for an operator. This study builds a time-dependent passenger demand-driven timetable synchronization and optimization (TDTSO) model as a mixed-integer programming model to minimize passenger total travel time in an urban subway network by adjusting departure times, running times, stopping times, and headways of all trains on each line. To solve the model, a binary variable determination (BVD) method is developed to calculate the binary variables of the TDTSO model, and a genetic algorithm based on the BVD method is proposed. The proposed TDTSO model is applied to the Beijing subway network in a case study. Several performance indicators are presented to verify the efficiency of the proposed model. The results can provide the operator of an urban subway network with additional options to produce a synchronized and optimized timetable for real-world situations.