Methods for optimizing station shunting operations

Abstract

To improve the transportation operations at Ulaanbaatar Railway Joint Venture Company (UBTZ JVC), which plays an important role in the social and economic sectors of Mongolia and is one of the key sectors in transportation, it is necessary to optimize the organization of shunting operations at stations lacking classification humps or yards, reduce inefficient costs, and improve the utilization of technical capacity. It is necessary to reduce the sorting and marshalling shunting operations performed to place wagons arriving for unloading onto branch tracks. Within the scope of this research, an integrated model adapted to local railway operations was developed by synthesizing the principles of movement and resource planning from traffic management theory, the workflow and decision-making structure of process organization theory, and the empirical, data-driven analytical approaches of Grounded Theory. Given that the construction of a classification hump requires substantial capital investment, this research focused on developing an optimization model based on key operational parameters, including train composition, destination stations, unloading duration, movement records, and cost structure. The data processing and analysis were performed in the Python programming environment to obtain quantitative results. The findings demonstrate that reducing waiting costs significantly decreases idle wagon time, shortens wagon turnaround duration, and enhances the utilization efficiency of the rolling stock fleet, thereby improving continuity and reliability in transport operations. In addition, the research identified strategic approaches for improving the process organization of train marshalling and wagon placement on branch tracks, and outlined the primary implementation phases of the proposed system. Potential operational risks- such as interruptions in shunting operations, employee resistance, and challenges in system integration- were also evaluated during the implementation planning stage.