Generally, to address the resource management issues in high-speed railway operations, particularly in the context of large-scale networked high-speed train transportation organizations, a phased optimization approach is introduced. This approach divides the problem into two stages: the high-speed train timetabling and the planning of Electric Multiple Unit (EMU) route. The lack of direct integration between these stages has hindered the flexible and efficient utilization of line capacity and EMU resources based on large-scale network, limiting the potential for mutual compensation and coordination among different types of resources across different regions. Furthermore, the coupling between interconnected resources has been overlooked. Compared to the aforementioned phased research areas, this study proposes an integrated optimization of train timetables and EMU routing plans in the context of networking. This study is capable of handling a large number of comprehensive optimization decision variables, which increase exponentially as the number of trains and EMUs considered grows. It thoroughly examines the importance of the linkage and coupling relationships between train timetables and EMUs, providing a new feasible method as the theoretical foundation. Adopting a resource linkage perspective, this paper employs complex system modeling, combined with empirical data from actual high-speed rail cases. This approach can significantly shorten the preparation period for high-speed train timetables and EMU routing plans, accelerating the frequency of updates and upgrades to high-speed rail passenger transportation services. To verify the feasibility and effectiveness of the proposed model and method, a case study was conducted on the EMU circulation plan and draft train timetable for the Beijing-Shanghai high-speed railway, with the results analyzed accordingly.

During the development of transportation infrastructure in China, the high-speed rail (HSR) network has been rapidly expanded, exerting a substantial impact on regional economic growth. While most existing studies on the HSR-economy relationship have focused on developed regions in eastern China, this study selects two major urban agglomerations in the relatively less-developed western region—the Guanzhong Plain Urban Agglomeration (GPUA) and the Chengdu-Chongqing Urban Agglomeration (CCUA)—as its study subjects. This study constructs a multi-layer network framework based on complex network theory and the gravity model, incorporating physical and operational HSR networks along with an economic network. By employing Social Network Analysis (SNA), the Mantel test, and the Time Exponential Random Graph Model (TERGM), we systematically examine the spatiotemporal evolution of the HSR network structure, its correlation with the regional economic network, and the associated mechanisms and effects. The results indicate that from 2014 to 2024, the density of the HSR network increased in both the GPUA and the CCUA. The GPUA maintained a single-core structure centered on Xi’an, while the CCUA exhibited a dual-core structure with Chengdu and Chongqing as hubs. The Mantel test confirms a significant positive correlation between the HSR operational network and the economic network. This correlation is stronger in the more economically developed and administratively concentrated CCUA—spanning just one province and one municipality—than in the cross-provincial GPUA. Further analysis by TERGM demonstrates the independent role of HSR in the development of economic networks and its transmission path. Correlation analysis further reveals that enhanced HSR connectivity and strengthened economic ties are not fully synchronized.

In China, there is a significant surge and fluctuation in the passenger flow of high-speed railways during holidays, and the holiday line plan is made by adding weekend/peak lines to the workday line plan. Therefore, finding a balance between the adaptability to passenger flow demand and such a relatively fixed line plan structure has become a difficult problem, which is a crucial factor in the sustainable operation of railway passenger transport. This paper first designs and proposes an algorithm for compiling the line pool of weekend and peak lines. By introducing the time dimension, a multi-day train service network is constructed. Then, an optimized model for the holiday line planning problem (HLPP) that comprehensively considers passenger flow demand and plan structure is established. Taking the Qingming Festival as an example, the results showed that among the trains with expanded formations in the optimized holiday line plan, short-distance trains accounted for nearly 70% and some long-distance trains was cancelled, reducing the operation cost by 4.46% compared to the actual plan. The train routing plan also maintains similarity to the weekday EMU circulation. It is demonstrated that the method proposed in this paper can achieve a better balance between efficient resource utilization and operational stability, enhancing the sustainable operability and profitability of the high-speed railway system.