Dynamic Scheduling Method of High-speed Trains Based on Improved Particle Swarm Optimization

During the operation of high-speed trains, high-speed rail trains often run turbulently due to bad weather, foreign objects intrusion, train failures, and other emergencies, resulting in the inability of high-speed trains to operate in accordance with the basic operation diagram. Aiming at the dynamic dispatching problem of late arrivals of high-speed rail trains, a mathematical model for the dynamic dispatching of high-speed rail trains at late train arrivals was established with the aim of minimizing the late arrival time of trains, late departures from stations, and the number of train delays. A dynamic weighted particle swarm optimization algorithm is proposed to solve the model. Taking Nanjing South to Cangzhou section as an example, simulation experiments were conducted under the conditions of changes in the number of trains, train delays, and late train stations. The experimental results show that the proposed algorithm can quickly restore the train to normal operation and has strong real-time and high efficiency.