Real-time optimization of containers and flatcars for intermodal operations

We propose a dynamic model for optimizing the flows of flatcars that considers explicitly the broad range of complex constraints that govern the assignment of trailers and containers to a flatcar. The problem is formulated as a logistics queueing network which can handle a wide range of equipment types and complex operating rules. The complexity of the problem prevents a practical implementation of a global network optimization model. Instead, we formulate a global model with the specific goal of providing network information to local decision makers, regardless of whether they are using optimization models at the yard level. Thus, our approach should be relatively easy to implement given current rail operations. Initial experiments suggest that a flatcar fleet that is managed locally, without the benefit of our network information, can achieve the same demand coverage as a fleet that is 10 percent smaller, but is managed locally with our network information.