AbstractScheduling trains in a railway network is a fundamental operational problem in the railway industry. This paper sets up multi-objective optimal model of train operation adjustment, whose optimization objective is to reduce the train delay time and the numbers of delay train. Since the model is established as an NP complete problem, a multi-objective particle swarm optimization algorithm (MPSO) is proposed to solve the complex problem. Considering the strategy of dispatcher’ preference, MPSO can get a set of Pareto solutions in the actual train operation adjustment problems. The actual experiment, taking Beijing-Shanghai high-speed railway as example, is conducted to validate the feasibility of the algorithm compared with the basic particle swarm optimization algorithm (PSO). Results demonstrate that the model can capture the characteristics of the practical dispatching problem. MPSO is efficient for train operation adjustment and provides better solutions than the traditional approaches.