Merging Flows and Optimizing Aircraft Scheduling in Terminal Maneuvering Area Based on GA

Akinori Murata (1) , Daniel Delahaye (2) , Keiki Takadama (1)

1 The University of Electro-Communications [Tokyo]
2 ENAC - Ecole Nationale de l'Aviation Civile

Runway capacity problem have been emerging in current overloaded congestion airports. This paper focuses on improving the runway capacity and resolution of conflicts of aircraft in terminal maneuvering area and proposes its method which can find the feasible solution using detour structure. In detail, our proposed method use alternative routes or sub-route as detour to avoid conflict and to change the position of arrival sequence. Through the intensive simulation on Paris Charles De-Gaulle airport, we revealed that our proposed method can find the efficient arrival sequence without conflict and detours contribute to optimize the landing sequence.

Mots clés: Air Traffic Control; Aircraft Merging Problem; Genetic Algorithm

Domaines: Mathématiques [math]; Optimisation et contrôle [math.OC]

Akinori Murata, Daniel Delahaye, Keiki Takadama. Merging Flows and Optimizing Aircraft Scheduling in Terminal Maneuvering Area Based on GA. ICRAT 2018, 8th International Conference for Research in Air Transportation, Jun 2018, Barcelone, Spain. ⟨hal-01823198⟩