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Ground delay program planning under uncertainty in airport capacity

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This paper presents an algorithm for assigning flight departure delays under probabilistic airport capacity. The algorithm dynamically adapts to weather forecasts by revising, if necessary, departure delays. The proposed algorithm leverages state-of-the-art optimization techniques that have appeared in recent literature. As a case study, the algorithm is applied to assigning departure delays to flights scheduled to arrive at San Francisco International Airport in the presence of uncertainty in the fog clearance time. The cumulative distribution function of fog clearance time was estimated from historical data. Using daily weather forecasts to update the probabilities of fog clearance times resulted in improvement of the algorithm's performance. Experimental results also indicate that if the proposed algorithm is applied to assign ground delays to flights inbound at San Francisco International airport, overall delays could be reduced up to 25% compared to current level.
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Keywords: air traffic management; air transportation; ground delay program; optimization

Document Type: Research Article

Affiliations: 1: University Affiliated Research Center,NASA Ames Research Center, Moffett Field, MS 210 – 8, Bldg. N210, Room 220Moffett Field,CA,94035, USA 2: Department of Civil and Environmental Engineering, 114 McLaughlin Hall,University of California, Berkeley,CA,94720, USA 3: Aviation Systems Division,NASA Ames Research Center, MS 210-15, Bldg. N210, Room 121Moffett Field,CA,94035, USA

Publication date: 01 August 2012

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