Railway transportation system faces the problem of tail gas emission while meeting the transportation demand, which puts forward higher requirements for energy saving and emission reduction. In order to meet this challenge, this paper proposes an intelligent optimal scheduling method based on improved genetic algorithm, and constructs a multi-objective optimization model to balance the transportation efficiency and tail gas emission. The effectiveness of the algorithm in reducing tailpipe emissions, improving transportation efficiency and shortening calculation time is verified through simulation experiments of actual railroad transportation network. The results show that the method has good optimization performance and practical application value, providing technical support for the green development of railroad transportation system.