A Train Timetable Optimization Method Considering Multi-Strategies for the Tidal Passenger Flow Phenomenon

The rapid growth of cities and their populations in recent years has resulted in significant tidal passenger flow characteristics, primarily manifested in the imbalance of passenger numbers in both directions. This imbalance often leads to a shortage of train capacity in one direction and an inefficient use of capacity in the other. To accommodate the tidal passenger flow demand of urban rail transit, this paper proposes a timetable optimization method that combines multiple strategies, aimed at reducing operating costs and enhancing the quality of passenger service. The multi-strategy optimization method primarily involves two key strategies: the unpaired operation strategy and the express/local train operation strategy, both of which can flexibly adapt to time-varying passenger demand. Based on the decision variables of headway, running time between stations, and dwell time, a mixed integer linear programming model (MILP) is established. Taking the Shanghai Suburban Railway airport link line as an example, simulations under different passenger demands are realized to illustrate the effectiveness and correctness of the proposed multi-strategy method and model. The results demonstrate that the multi-strategy optimization method achieves a 38.59% reduction in total costs for both the operator and the passengers, and effectively alleviates train congestion.