## 1 Introduction  
There has been rapid development of the high-speed railways over the past few decades. With the expansion of the railway network and passenger demand, railway operators are facing more challenges in providing higher quality services to passengers.  
Fulfilling passenger demand and providing transportation services accurately for the demand is the core problem in high-speed railways. Currently, railway operators have been using a 'planning-based' mode to provide transportation services, which forecasts the passenger demand for a certain time period and prepares train plans to match the infrastructure resources with the forecasted demand as much as possible. However, passenger demand typically has an uneven distribution, with highly heterogeneous spatial flow patterns and flow sizes, especially during the COVID-19 pandemic. Dynamic transport demand has not been accurately and opportunely grasped by operators. As a result, there are two phenomena occurring on the network simultaneously: \"hard to get tickets\" and \"excess capacity\".  
To better respond to the passenger demand, the railway operators have been making unremitting efforts, aiming to adapt to the time-varying passenger demand by constantly shortening the adjustment period of train schedules. However, due to the low accuracy of passenger travel demand forecast, 'planning-based' train operation planning is always flawed during time horizons, when the passenger demand fluctuates greatly. A new 'demand-responsive' train planning concept provides an important idea to match passenger demand and transport resources dynamically to solve this problem. Its core mechanism is to improve the information exchange between the supply and demand sides. Once the travel demand information of passengers is obtained, the railway operators will respond to provide a service plan with a more effective allocation of resources.  
Train planning is important to guarantee the safety and efficiency of transport services for the high-speed railway system. Its main task is to develop a series of train operation plans based on passenger demand during different time periods, to better make rational utilization of railway infrastructure resources. In general, the train planning process of the high-speed railway system is decomposed into railway network planning, railway line planning, train timetabling, rolling stock scheduling, crew scheduling and real-time management [1], shown in Figure 1.  
As two important parts of train planning, both stop planning and train timetabling have significant effects on train operation and service quality. Stop planning, which determines the stop pattern of all trains, is an important factor in line planning. The departure and arrival times of each train at each station are determined in the process of timetabling. Thus, system efficiency, capacity utilization and sensitivity to delays regarding travel times are highly dependent on stop plans and timetables. Under demand-responsive transport, train planning also faces new challenges. Normally, the above two parts are arranged in a sequential and progressive manner, as shown in Figure 1. However, with a predetermined stop plan, the solution space for solving the timetabling problem is reduced. The phased design of stop planning and train timetabling usually cannot generate a best solution with time-dependent passenger flow demand. Therefore, it is necessary to optimize the integration of both stop planning and train timetabling for demand-responsive transport in high-speed railways.  
Figure 1: Railway planning process.