A data driven operations research approach to intermodal rail transportation load and block capacity planning problems

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Intermodal transport refers to the transportation of freight in containers using more than one mode of rail, ship and truck. This project focuses on optimizing the planning and operations of intermodal rail transportation. Canadian railway companies are both network and terminal operators and hence face many complex large-scale optimization problems. Many of these problems have been studied in the operations research (OR) literature for decades but the gap between state-of-the-art and state-of-practice is huge. The railway industry heavily relies on the experience of human resources rather than mathematical models even though the literature reports potential savings in the order of millions of dollars annually by using optimization models. This project addresses this gap by proposing methods to deal with two complementary problems currently faced in intermodal rail transportation, namely, load planning under uncertainty and block capacity planning. We address these problems by combining demand models and OR methods.