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Strategic flight planning models based on integer programming: Optimizing air traffic and airport capacity
- 1 Civil Aviation University of China
- 2 Civil Aviation University of China
- 3 Civil Aviation University of China
* Author to whom correspondence should be addressed.
Abstract
In the context of limited airport capacity, the increasing imbalance between growing air traffic demand and constrained airport capacity significantly elevates the probability of flight delays or even cancellations. To address this issue, this paper proposes a strategic flight planning model based on integer programming from the perspective of airport capacity. The model incorporates constraints such as departure, arrival, and total capacity, aiming to adjust flight schedules at the strategic phase to more effectively utilize existing airport resources. Taking the example of adjusting flight schedules from Chengdu Shuangliu International Airport, direct to Tengchong Tuofeng Airport, to Chengdu Shuangliu International Airport first and then to Dehong Mangshi International Airport, the paper demonstrates, through strategic flight planning, a more balanced alignment of flight demand and airport capacity without increasing the burden on the airport. This validates the practicality and effectiveness of the proposed model. The research results indicate that the model can effectively improve abnormal flight situations while reducing operational costs, providing significant convenience for airports, airlines, and passengers.
Keywords
strategic flight planning, flight delay, traffic demand, airport capacity, integer programming model
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Cite this article
Ye,Z.;Pang,Q.;Hu,L. (2024). Strategic flight planning models based on integer programming: Optimizing air traffic and airport capacity. Applied and Computational Engineering,65,210-221.
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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of Urban Intelligence: Machine Learning in Smart City Solutions - CONFSEML 2024
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