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| Title: | Stochastic Models for the Estimation of Airport Arrival Capacity Distributions |
| Authors: | Inniss, Tasha |
| Department/Program: | ISR
NEXTOR |
| Type: | Dissertation |
| Keywords: | Societal Infrastructure Systems |
| Issue Date: | 2001 |
| Series/Report no.: | ISR; PhD 2001-3
NEXTOR; PhD 2001-1 |
| Abstract: | In this dissertation, statistical and integer programming methods are used to calibrate models to estimate airport arrival capacity distributions. These distributions are an essential input to decision models used to regulate flow into congested airports when demand for arrival resources exceeds the available capacity. <p>The techniques developed make contributions to the body of knowledge on air traffic flow management. On a more general level, the approach developed can be viewed as a clustering technique that maintains the time order of imbedded time series data. <p>During instances of capacityﬤemand imbalances, efficient planning and decisionשּׂaking is contingent upon the "goodness" of the models that estimate airport capacity over time. Airport capacities are subject to substantial uncertainty as they depend on stochastic weather conditions. The models developed in this thesis are required inputs into a class of stochastic ground holding models that determine the amount of ground d... |
| URI: | http://hdl.handle.net/1903/6256 |
| Appears in Collections: | Institute for Systems Research Technical Reports
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| PhD_2001-3.pdf | | 2334Kb | Adobe PDF | 166 | View/Open |
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