DEVELOPING A FRAMEWORK TO OPTIMIZE THE OPERATIONS OF AN INTERMODAL UNDERGROUND FREIGHT TRANSPORTATION TERMINAL USING SIMULATION

According to the U.S. Department of Transportation (USDOT), by 2040, nearly 30,000 miles of our busiest highways will be clogged daily and it is important to increase the capacity of our transportation system. Construction of intermodal underground freight transportation (UFT) systems for freight movement through underground pipelines or tunnels, can increase the capacity of the existing shipping network. The intermodal terminal is a major component of the UFT’s innovative infrastructure project. Increasing demand for container transportation systems in terminals will raise the risk of terminal congestion and delivery delay due to the increase in freight transportation system bottlenecks (traffic jams and extended terminal loading and unloading wait time) without an equivalent increase of stacking and handling capacity. Thus, it is essential to evaluate the current terminal capacity by studying the effect of different operational components on terminal performance. The objective of this dissertation is to develop a framework for optimizing the capacity of intermodal UFT terminals with discrete event simulation (DES) model. The terminal operations considered include speed, headway, number of gondolas (equipment used for carrying the freight) needed to carry containers, line capacity, number of handlers, stack-yard capacity, the conveyance system (tracks and power requirements), lifting equipment, and drayage performance. The expected annual shipped containers for the UFT system research case study is calculated mathematically and then the UFT system is simulated to build the base-model for this dissertation. The base-model validity is examined referring to the model output for the annual number of shipped containers and the results are confirmed for base-model validity. For optimizing terminal operations, two different scenarios were simulated to test the variations of performance indicators. The first scenario considers a terminal with a stack-yard in the form of two small loops and the second scenario is in the form of one large loop without a stack-yard. The outputs for all three models base model, scenario number one, and scenario number two are compared with the UFT annual expected shipped containers. The results show the number of shipped containers for Scenario No. 1 and Scenario No. 2 are respectively 34% and 59% more than the annual expected shipped containers, which are 46% and 73% more than the base-model output. The findings confirmed that the percentage of bottlenecks in both scenarios with a lower cycle time—compared to the base-model—significantly decreased. Additionally, Scenario No. 2 without a stack-yard (compared with Scenario No. 1) can handle 25% more containers per year.