Strategies for Effective Rail Track Capacity Usage

In the United States, railways are the major means to trans-continentally move goods from ports to the various inland destinations. Due to mergers and abandonment of rail lines, there has been a reduction in the track capacity, concentrating rail traffic to fewer lines. In addition to this, booming trade with Pacific Rim nations has seen the annual trade in the Ports of Los Angeles and Long Beach exceed 100 million tons with anticipation to double and possibly triple their cargo by 2020 (Leachman, 2002). The growth in the number of containers has already introduced congestion and threatened the accessibility and capacity of the rail network system in the Los Angeles area. Average transit times have stretched out in many corridors. There is clearly a need among US freight railroads for better analytical tools to manage their capacity and scheduling. A challenging problem is determining the effect of shipments on a railroad, including estimation of the travel times and delays in the network plus determination of the most efficient method of scheduling these loads. This entails the ability to assign trains to routes based on the statistical expectation of running times in order to balance the railroad traffic, and to reject or defer shipment requests that would overload the network. In the first year of this research, we used mathematical modeling techniques to perform the former, that is, to be able to route and schedule trains on a railway network so as to minimize the travel time delays. In the second year we developed a simulation-based delay estimation methodology that would be able to estimate the travel-time delay over any given single-track or double-track rail network. These estimates can be used to reject or defer shipments that could cause congestion in the network. Efficient solutions to the above problems are necessary to obtain an effective capacity planning and scheduling system for train networks. As a whole, this research represents an original effort in developing the first quantitative model to accept, defer or reject shipments on a railroad, with decisions based on an accurate representation of the delays these shipments cause on the railroad and the possibility of real-time rerouting trains to alternative tracks. ii Contents Disclaimer i Abstract ii Disclosure 1 Acknowledgements 2