Optimization Research of High-Speed Railway EMU Utilization Schedule Based on Three-Dimensional Space-Time Network

With the continuous improvement of China High-Speed Railway network and the large number of EMUs being put into operation, it is essential to conduct in-depth research on the preparation and optimization of EMU operation schedules from the perspectives of energy consumption and carbon emissions during the operation and maintenance phases, in order to achieve the carbon peaking and carbon neutrality goals in the transportation sector. Firstly, addressing the space-time dynamic characteristics of EMU operation schedules, a three-dimensional space-time network model of EMU operation schedules is established by adding the maintenance status dimension to the traditional two-dimensional space-time network model. By utilizing the connection changes of different operational status arcs in the three-dimensional space-time network, important information such as the maintenance status, maintenance frequency, and carbon emissions can be clearly and effectively presented, thus fully and accurately describing the entire operation and maintenance process of the EMUs. Next, considering the maintenance requirements of the EMUs, connection time constraints, status arc occupation constraints, operation arc conflict resolution constraints, and other conditions, an optimization model for High-Speed Railway EMU operation schedules based on the three-dimensional space-time network is established. The objective is to minimize the total EMU operation time, reduce maintenance frequency, and achieve the balanced carbon emission level. A three-dimensional array coding NSGA-II genetic algorithm has been designed to solve the model. This algorithm employs a crossover strategy that retains cross information, maximizes the retention of non-cross information, and conditionally regenerates. Finally, the model and algorithm's effectiveness is verified using relevant data from the Beijing-Shanghai High-Speed Railway EMU operation schedules. The results indicate that the optimization model and algorithm, grounded in the three-dimensional space-time network, not only accurately depict the entire operation and maintenance lifecycle of the EMUs, but also significantly enhance their operational efficiency and benefits, reduce the number of EMUs in operation, and mitigate carbon emissions. This research can provide a valuable reference for High-Speed Railway operation and management departments in formulating or optimizing EMU operation schedules.