The authors employ correlation and comparative analyses to identify dependencies among the analyzed indicators, thereby establishing the nature of their mutual relationships. Simulation models based on dynamic programming utilize mathematical methods to determine optimal solutions. This is evidenced by a determination coefficient of 0.0911 observed between the downtime of a local station car and the working fleet indicator in certain cases. Regression analysis revealed that the relationships among the station’s primary operational parameters are highly nonlinear. This research assesses the functionality of the Republic of Uzbekistan’s freight railway infrastructure. The analysis of the operations of the Tashkent-Tovarnaya freight station indicates a need to explore options for improving the station’s organization and functional reliability. These improvements aim to achieve effective coordination of car flows despite their uneven distribution.