Article ID: | iaor1995186 |
Country: | United States |
Volume: | 27 |
Issue: | 3 |
Start Page Number: | 266 |
End Page Number: | 280 |
Publication Date: | Aug 1993 |
Journal: | Transportation Science |
Authors: | Jarrah Ahmad I.Z., Yu Gang, Krishnamurthy Nirup, Rakshit Ananda |
Keywords: | artificial intelligence: decision support |
Aircraft shortages occasionally occur during day-to-day airline operation due to factors such as unfavorable weather conditions, mechanical problems, and delays in the schedule of incoming flights. Flight controllers need to respond to such shortages on a real-time basis by delaying or cancelling flights, swapping aircraft among scheduled flights, or requesting the usage of surplus aircraft. The choices undertaken aim at minimizing the losses incurred while retaining an operable flight schedule. In this paper, the authors represent two network models for aiding flight controllers in this complex decision environment. The models represent an attempt at conceptualizing this important and relatively unstudied problem, and form the basis for an evolving decision support sytem at United Airlines.