Managing Uncertainty in the Single Airport Ground Holding Problem Using Scenario-based and Scenario-free Approaches

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Civil and Environmental Engineering)--University of California, Berkeley, 2007 - 342 pages
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Recent developments in solving the single airport ground holding problem (SAGHP) use static or dynamic stochastic programs to manage uncertainty about how airport capacities will evolve. Both static and dynamic models involve the use of scenarios that depict different possible capacity evolutions. Dynamic models also require scenario trees featuring branch points where previously similar capacity profiles become distinct. In this dissertation, we present methodologies for generating and using scenarios and scenario trees from empirical data and examine the performance of scenario-based models in a real-world setting. We find that most U.S. airports have capacity profiles that can be classified into a small number of nominal scenarios, and for a number of airports these scenarios can be naturally combined into scenario trees. The delay costs yielded from using dynamic optimization are found to be consistently and considerably lower than that from static optimization. However, the costs incurred from applying scenario-based optimization, either static or dynamic, to these airports is considerably higher than what the "theoretical" optimization results suggest, because actual capacities vary around the nominal values assumed in the optimization, and because of uncertainty in navigating scenario trees that the idealized models ignore.

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