Production Team Scheduling in Railroad Networks

U.S. railroad companies spend billions of dollars every year on track maintenance in order to ensure safety and operational efficiency. Optimizing the production team (i.e., large maintenance team) schedule is a very complex problem with major cost implications. Currently, the decision making process for production team scheduling is largely manual and primarily relies on the knowledge and judgment of experts. This paper addressed the production team scheduling problem by formulating it as a time-space network model with many types of side constraints. Multiple neighborhood search algorithms were proposed to solve the model. The proposed approach has been applied to real-world problem instances. The comparison with manual solutions has indicated the proposed approach significantly outperforms the manual solution practice in the industry. The proposed approach has been adopted by a Class I railroad to help in its decision making process and reduce costs.