# An Integrated Optimization Method of High-Speed Railway Rescheduling Problem at the Network Level
## 2 Literature Review
[PERSON] only considered canceling train services in the case of a serious disturbance. [PERSON] et al. [14] provided an integer linear programming model of real-time adjustment for train operation in view of the serious interruption in high-speed railways in China and designed a two-stage algorithm to get the overall feasible solutions. Then [PERSON] et al. [15] studied the adjustment of train timetables under the condition of a complete interruption of train operation. [PERSON] et al. [16] constructed the train routing selection problem under the condition of emergencies as a mixed-integer programming model. First, they used an ant colony algorithm to solve the feasible route of the train and then adjusted the train timetable based on the obtained feasible route under the condition of emergencies. Finally, they tested the effectiveness of the model and algorithm on the railway lines in France. Train sets circulation plan is the premise of train timetable execution. Meanwhile, available train sets become scarce in emergency conditions; therefore, a number of studies have focused on train set circulation plans under emergency conditions in order to optimize the plan and save train set resources. [PERSON] et al. [17] proposed a mixed-integer linear programming model to solve the train rescheduling problem, taking into account the dispatching of train sets during emergencies and after the resumption of train operation. [PERSON] [18] et al. built a model based on the train operation route to optimize the train operation plan during the recovery period caused by an emergency and used a branch and price method to solve the model. [PERSON] et al. [19] established a mixed-integer linear programming model to solve the problem of train timetable rescheduling in the case of a complete interruption. The model can calculate and give the most suitable route, track, and station to turn back. They solved the model by [PERSON] and then tested it on two railway lines in the Netherlands. Some studies considered the train set circulation plan and train timetable together; most of them used a two-stage method, and a few of them explored an integrated adjustment method for the train timetable and train set circulation plan. Based on the feasible train set circulation, [PERSON] et al. [20] used a branch and price method to realize the coordination of the train set circulation plan and train timetable. Different from [PERSON] et al. [20], [PERSON], [PERSON] et al. [21] integrated the timetable scheduling problem and the rolling stock scheduling problem through a big-M formulation, and the trains are allowed to operate in a platoon according to passenger demand. [PERSON] et al. [22] constructed a collaborative adjustment method that can adjust the train operation plan according to passenger demand and then adjust the train timetable and train set circulation plan under emergency conditions. [PERSON] et al. [23] studied the coordination of train timetables and train set circulation plans in the programming stage, and [PERSON] et al. [24] studied that after emergencies. Compared with the two-stage method, the integrated optimization method can better balance the close coupling relationship between the train timetable and the train set circulation plan and provide more reasonable solutions. From the perspective of the algorithm, many algorithms are widely applied to solve the rescheduling problem, such as [20] branch and price algorithm, [25] ant colony algorithm, [26] heuristic simulated-annealing algorithm, etc. [1,5]. Both use particle swarm optimization algorithms; the difference is that [1] used particle swarm with quantum-inspired algorithms, and [5] used particle swarm optimization algorithms with genetic algorithm (GA). In recent years, artificial intelligence has been applied to the transportation field. [27] used a random forest algorithm to predict train delays.