At the present time, millions of dollars are being lost by major airlines each year because of the inability of high density air terminals to efficiently service all of the demands placed upon them during peak periods of demand. Up to the present time, studies involving congestion have been aimed primarily at the implementation of computerized techniques to aid the air traffic controller during peak demand periods. By scheduling aircraft in a given system in a different manner, delay, caused by congestion, could possibly be reduced at high density terminals even more than it has been reduced by the results obtained from previous studies.
The approach taken in this study involves testing different heuristic scheduling algorithms, based on what has been done previously, to determine what extent total system delay can be reduced. The method of approach which was followed was based on a simulator which models aircraft movement between N major terminals. For each scheduling algorithm developed, hourly statistics related to the number of aircraft demanding service, average departure delay, and average arrival delay were calculated along with total system delay times for arriving and departing aircraft. The results obtained from these algorithms were analyzed and compared with the scheduling algorithm which resulted in a reduction in delay being examined in greater detail to determine whether or not such a schedule would actually be feasible and worthwhile. / Master of Science
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/45543 |
| Date | 09 November 2012 |
| Creators | Crockett, Randal R. |
| Contributors | Industrial Engineering and Operations Research, Schmidt, J. William, Bennett, G. K., Taylor, Robert E. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Thesis, Text |
| Format | ix, 232 leaves, BTD, application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | OCLC# 21996924, LD5655.V855_1974.C75.pdf |
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