Scheduling under uncertainty for a Single-Hub Intermodal Freight System
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This thesis addresses the optimization of an intermodal system with freight transfers at a single hub. It investigates the transportation processes and constraints that arise in a system's recovery after a major disruption during which backlogs have accumulated along the routes. When dealing with the backlogs, the system operator must coordinate the transportation processes and control the inflow of freight to the terminal in order to avoid overloading its storage facilities, which might reduce the throughput of the system. The coordination of transportation processes during the system's recovery can further improve the overall system performance by reducing the dwell time, increasing vehicle utilization and reducing late delivery penalties. This work focuses on the scheduling problem and develops an approach that would help the system operator reduce the overall system cost while taking into account the constraints arising in actual intermodal and intra-modal systems. Assuming that the schedule on some routes is exogenously determined and inflexible, we seek to optimize the schedules of vehicles on remaining routes.
Models are developed that minimize the total cost of operating an intermodal system with freight transfers at one hub by optimizing the departure times of vehicles on the routes with flexible schedules. This model can be solved numerically without the approximations of alternative methods such as simulation. Moreover, it can be successfully applied to situations when statistical or queuing analyses are not applicable due to the small number of events (vehicle arrivals). We specifically analyze an intermodal system consisting of multiple feeder truck routes and multiple main airline routes. The specific example of two transportation modes was used to make the development and application of the model easier to understand. However, the mathematical model developed in this thesis is applicable to any other combination of transportation modes using discrete vehicles.