Study on Train Operation Adjustment Based on Hybrid Convergent Particle Swarm Optimization

Train operation adjustment is an important part of the railway dispatch work, which is the core work to assure the transportation order and efficiency. The essence of the adjustment is to adjust the train to run according to the planned schedule. In this paper, a train operation adjustment model is built and the hybrid convergent particle swarm optimization is employed to solve the optimizing problem. It not only satisfies the constraints of train operation adjustment, but also has the real-time adjusting ability. Computing results are changed into a train operation adjustment plan. It is concluded that the algorithm has excellent performance, compared with the basic swarm algorithm. The train operation adjustment plan is practical and efficient.