Balakrishnan, JaydeepEspey, Renae Lorelei2016-05-122016-05-122012-02RL Espey and J Balakrishnan The Journal of the Operational Research Society Vol. 63, No. 2 (FEBRUARY 2012), pp. 139-15001605682http://hdl.handle.net/1880/51197Link to Publisher's version of the article http://www.jstor.org/stable/41353917 Pre print deposited 05/12/2016 Accepted for publication in the Journal of the Operational Research Society, October 2010.Canadian railway companies operate in a capital intensive segment of the transportation industry. In most railway companies, the covered hopper railcar fleet is one of the larger fleets due to its use in moving grain and potash, commodities that move large volumes of product. This railcar fleet is also difficult to manage due to demand seasonality and joint commodity use. This paper demonstrates how an aggregate planning model can be used to support decision-making related to optimization of covered hopper railcar storage. Exploratory research prior to model development involved interviews with company personnel. The model was developed through quantitative research and implemented using spreadsheet optimization. The results indicate that using this model can reduce the total cost of storage through effective planning. The model also provided insight to improve railcar storage such as the elimination of excess storage locations and the need to do further investigation. The company is in the process of implementing suggestions from this paper.enaggregate planningstoragespreadsheet optimizationmathematical programmingrailwaystransportjournal article10.11575/PRISM/34162