This study addresses the pressing need for efficient and intelligent methods in high-speed railway express cargo transportation, particularly in the context of China’s rapid expansion in this sector. Recognizing the importance of two-sided matching problems in various fields, we propose an innovative approach to match high-speed railway trains with cargo, enhancing transportation efficiency and space utilization. This approach involves classifying and analyzing cargo attributes, followed by the implementation of a two-sided matching algorithm that considers various constraints such as departure schedules, cargo types, and specific vehicle requirements. By leveraging high-speed railway networks for small-batch, multi-batch, and real-time transportation, this project aims to optimize freight plans, maximize resource utilization, and boost economic efficiency. The research, given the urgent needs for the development of reality, is of great theoretical and practical significance to promote the development of theory in this field and to fill the technical gap.