Demand-driven train timetabling for air and intercity high-speed rail synchronization service

Synchronizing air and intercity high-speed railway (A-IHSR) services has recently been developing vigorously. Train timetables are critical for improving A-IHSR synchronization. This paper proposes a method to optimize intercity high-speed railway (IHSR) timetables based on the dynamic passenger demand of the A-IHSR. An integer non-linear programming (INLP) model is formulated to minimize the passenger waiting time, in which rigorous train capacity, oversaturation situation, and skip-stop are also taken into consideration. We also extend the train timetabling model by considering the synchronization events of flight-train and the train circulation plan. Then, this model is reformulated as a relaxed non-linear programming (NLP) model. . A multimodal nomad algorithm (MNA) is proposed to solve it. The train circulation plan solves by the Gurobi solver. A numerical experiment based on data of the operation of the Jinnan–Binzhou HSR is implemented to demonstrate the efficiency and performance of our proposed model and algorithm.