Train Timetable and Trajectory Optimization Using Improved State-space MILP

Energy consumption in railway sectors is mainly dominated by train control and the timetable. This paper mainly discusses an energy-efficient train timetabling (EETT) method, which is under the total travel time limit and considers the energy-efficient train control (EETC) between consecutive stations. First, a non-linear EETC model is transformed into a mixed integer linear programming (MILP) model by discretization and linearization. Then, in order to improve the performance of MILP solver, especially the computational efficiency, a state-space improvement strategy is introduced, which could exclude those non-optimal state-spaces. Finally, two comparative simulations of HSRs are given. The results show that the proposed method not only can reduce the total energy consumption but also can reduce the computation time.