PROBLEMS ORIGINATING FROM THE PLANNING OF AIR TRAFFIC MANAGEMENT INITIATIVES

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dc.contributor.advisorBall, Michael Oen_US
dc.contributor.authorEstes, Alexanderen_US
dc.contributor.departmentApplied Mathematics and Scientific Computationen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2018-09-12T06:03:21Z
dc.date.available2018-09-12T06:03:21Z
dc.date.issued2018en_US
dc.description.abstractWhen weather affects the ability of an airport to accommodate flights, a ground delay program is used to control the rate at which flights arrive at the airport. This prevents excessive congestion at the airport. In this thesis, we discuss several problems arising from the planning of these programs. Each of these problems provides insight that can be applied in a broader setting, and in each case we develop generalizations of these results in a wider context. We show that a certain type of greedy policy is optimal for planning a ground delay program when no air delays are allowed. More generally, we characterize the conditions under which policies are optimal for a dynamic stochastic transportation problem. We also provide results that ensure that certain assignments are optimal, and we apply these results to the problem of matching drivers to riders in an on-demand ride service. When flights are allowed to take air delays, then a greedy policy is no longer optimal, but flight assignments can be produced by solving an integer program. We establish the strength of an existing formulation of this problem, and we provide a new, more scalable formulation that has the same strength properties. We show that both of these methods satisfy a type of equity property. These formulations are a special case of a dynamic stochastic network flow problem, which can be modeled as a deterministic flow problem on a hypergraph. We provide strong formulations for this general class of hypergraph flow problems. Finally, we provide a method for summarizing a dataset of ground delay programs. This summarization consists of a small subset of the original data set, whose elements are referred to as "representative" ground delay programs. More generally, we define a new class of data exploration methods, called "representative region selection" methods. We provide a framework for evaluating the quality of these methods, and we demonstrate statistical properties of these methods.en_US
dc.identifierhttps://doi.org/10.13016/M2KP7TV70
dc.identifier.urihttp://hdl.handle.net/1903/21311
dc.language.isoenen_US
dc.subject.pqcontrolledMathematicsen_US
dc.subject.pqcontrolledOperations researchen_US
dc.subject.pqcontrolledTransportationen_US
dc.subject.pquncontrolledAir Traffic Flow Managementen_US
dc.subject.pquncontrolledCombinatorial Optimizationen_US
dc.subject.pquncontrolledData Analysisen_US
dc.subject.pquncontrolledNetwork Flowen_US
dc.subject.pquncontrolledStochastic Optimizationen_US
dc.subject.pquncontrolledUnsupervised Learningen_US
dc.titlePROBLEMS ORIGINATING FROM THE PLANNING OF AIR TRAFFIC MANAGEMENT INITIATIVESen_US
dc.typeDissertationen_US

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