Rail transit express and local train schedule optimization considering hybrid rolling stock composition

This study adopts a hybrid rolling stock composition strategy and proposes a mixed-integer linear programming (MILP) model to optimize the rolling stock compositions together with the train timetable according to real-life passenger demand. The optimization objectives are to minimize the number of stranded passengers and rolling stocks. Two types of constraints are included: constraints related to timetabling and constraints related to passenger assignment. In addition, timetable optimization is used for mixed traffic, including local and express train services. Express trains overtake local trains at specific stations; therefore mapping constraints are built to match each train service to the corresponding train order at different stations to ensure a correct passenger assignment. Numerical examples based on the Shanghai Metro Line 16 are implemented to demonstrate the efficiency of the proposed model. The optimization results show that the proposed method can efficiently reduce the number of stranded passengers and the number of rolling stocks required.