A two-layer optimization model for high-speed railway line planning

Line planning is the first important strategic element in the railway operation planning process, which will directly affect the successive planning to determine the efficiency of the whole railway system. A two-layer optimization model is pro-posed within a simulation framework to deal with the high-speed railway （HSR） line planning problem. In the model, the top layer aims at achieving an optimal stop-schedule set with the service frequencies, and is formulated as a nonlinear program, solved by genetic algorithm. The objective of top layer is to minimize the total operation cost and unserved passenger volume. Given a specific stop-schedule, the bottom layer focuses on weighted passenger flow assignment, formulated as a mixed integer program with the objective of maximizing the served passenger volume and minimizing the total travel time for all passengers. The case study on Taiwan HSR shows that the proposed two-layer model is better than the existing techniques. In addition, this model is also illustrated with the Beijing-Shanghai HSR in China. The result shows that the two-layer optimization model can reduce computation complexity and that an optimal set of stop-schedules can always be generated with less calculation time.