Rolling Stock Allocation and Timetabling for Urban Rail Transit Network with Multiple Depots

Abstract

Rolling stock management and train timetabling are two challenging but very related issues in urban rail systems. The former is to allocate a certain fleet of trains to each depot, and the latter determines the arrival and departure times of train services according to the available rolling stock at each depot. While most existing studies consider these two tasks for a single line, this study focuses on the integrated optimization of rolling stock allocation, train timetabling, and rolling stock circulation for a whole network, where each depot can serve multiple connected lines and the trains can change lines in one operational cycle (i.e., one day). A time-space network is constructed to model the rolling stock circulation among multiple lines and depots, and a novel integer linear programming model is proposed to jointly optimize the allocation of rolling stock and train timetables for the involved lines. The objective function maximizes the service quality provided to passengers with minimized rolling stock investment cost. Numerical experiments based on the real-world data of the Beijing rail transit network are conducted to validate the effectiveness of this approach. The results demonstrate that the proposed approach can reduce the fleet size of rolling stock by 5% while providing the same service quality to passengers.