Currently, increasing the efficiency of maneuvering operations at sorting stations is one of the key tasks in transport logistics. Traditional methods of controlling shunting processes are often associated with high energy costs and insufficient automation at stations. These problems lead to an increase in operating costs and a decrease in the overall productivity of the stations. In connection with the development of intelligent transport systems, there is an opportunity to significantly improve the management of shunting operations, reduce energy costs and increase the environmental safety of railway transport. The purpose of this work is to offer intelligent and energy-efficient solutions aimed at optimizing maneuvering operations and increasing their efficiency. To solve this problem, it is necessary to apply a comprehensive method, which includes the introduction of intelligent transport systems and energy-efficient technologies. One of the effective methods for optimizing the management of maneuvering operations is the use of genetic algorithms, which are able to solve the task of finding the best solutions in complex systems with many variables. This approach will allow to optimize the management of maneuvering operations based on automated solutions, use of real-time data to minimize energy consumption.