Even though rail transportation is one of the most fuel efficient forms of surface transportation, fueling costs are the single highest operating cost head for railroad companies. For larger companies with several thousands of miles of rail network, the fuel costs often run into several billions of dollars annually. The railroad fueling problem considered in this paper has three distinct cost components. Fueling stations usually charge a location dependent price for the fuel in addition to a fixed contracting fee over the entire planning horizon. In addition, railroad company must also bear incidental and notional costs for each fuelling stop. This paper proposes a mixed integer linear program model that determines the optimal strategy for contracting and purchase schedule decisions that minimizes overall costs under certain reasonable assumptions. This model is tested on a large, real-life problem instance. Model performance was significantly enhanced by decomposition and introducing several MIP cuts. This paper compares the efficiency of different MIP cuts in order to reduce the run-time. Lastly, the paper concludes with an observation that even though the problem scale was expected to diminish the model performance, it was indeed noted that run-time and memory requirements are fairly reasonable.