An intelligent optimization system for terminal traffic management

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An intelligent optimization system for terminal traffic management

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2013-12

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This dissertation presents the development of a terminal traffic flow management system using an intelligent optimization method. The system is in an effort to provide advisories to efficiently assign runways to cope with the unbalanced traffic flow from and/or toward different directions and computes the optimal arrival or departure time for each flight. This is a high fidelity advisory system to assist traffic managers at airports to manage the complex terminal traffic in a more efficient fashion in order to ultimately minimize the overall flight delay in the entire airport and maintain a high level of safety at the same time. Multiple objectives pertaining to overall airport throughput, system delay, maximum individual delay, and runway balance are used. The system described in this study utilizes knowledge base intelligent optimization methods and takes advantage of the self-contained mixed integer linear program. The mixed integer linear program calculates the optimal schedule for each aircraft for each runway while the intelligent optimization method is used to produce optimal runway assignment for all flights in the entire airport. The importance of improving airport efficiency is introduced in detail in this dissertation. The system explicitly considers eliminating mid-air crossings within the terminal airspace due to irrational runway assignments. This not only improves safety but also effectively reduces controller workload. The importance and contribution of the study is addressed. This system is suitable for an airport with multiple runways. Simulations were conducted based on the real traffic mix for four of the 30 busiest airports in the United States and the results of the simulation prove the feasibility of the system. Future development of the system is also discussed.

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University of Minnesota Ph.D. dissertation. December 2013. Major: Aerospace Engineering and Mechanics. Advisor: Yiyuan J. Zhao. 1 computer file (PDF); xi, 86 pages.

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Lee, Hoilun Helen. (2013). An intelligent optimization system for terminal traffic management. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/162500.

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