By Topic

Study of Air Traffic Flow Management Optimization Model and Algorithm Based on Multi-objective Programming

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Wen Tian ; Coll. of Civil Aviation, Nanjing Univ. of Aeronaut. & Astronaut., Nanjing, China ; Minghua Hu

Because of more and more flight delays due to the increasing air traffic demands, merely depending on a mono-objective programming to solve problems such as departure slot, flight route and air traffic control (ATC) workload cannot meet the need of the air traffic flow management. In this paper, a multi-objective and non-linear model is developed, comprehensively considering the problems above and picking up factors causing airspace congestion and flight delays. Then, a multi-objective genetic algorithm is designed to solve this model. The simulation results based on the operational flight data prove that the model and the algorithm cannot only optimize the departure time and route for each flight within reasonable time-horizon, but also reduce the ATC workload. It makes air traffic flow management coincident with the actual operation, and finally effectively reduces the airspace congestion.

Published in:

Computer Modeling and Simulation, 2010. ICCMS '10. Second International Conference on  (Volume:2 )

Date of Conference:

22-24 Jan. 2010