Towards an Operational Sectorisation based on Deterministic and Stochastic Partitioning Algorithms

Judicaël Bedouet (1) , Thomas Dubot (1) , Luis Basora (1)

1 ONERA - The French Aerospace Lab [Toulouse]

This paper describes a method combining operational deterministic and stochastic approaches to generate optimised and smooth sector configuration plans. First, sector configurations commonly used within an Area Control Centre (ACC) are sorted according to a set of objectives for each time period. From these Pareto-optimal solutions, we determine through a stochastic method new sector configurations, mainly unstructured, to improve criteria such as the workload distribution. Then these optimized configurations are remodelled with another stochastic function to compute a set of final configurations acceptable to air traffic controllers. Secondly, we integrate these good solutions throughout the day to build the smoothest sector configuration plan possible, using the minimization of a dedicated distance function between successive configurations. Results of the SESAR 07.05.04 VP-755 experiments demonstrate that such methods could improve several criteria at the level of an ACC, such as the French Reims ACC, and pave the way for the development of an automated decision support tool integrating such algorithms.

Mots clés: SESAR; OPTIMISATION

Domaines: Algorithme et structure de données [cs.DS]

Judicaël Bedouet, Thomas Dubot, Luis Basora. Towards an Operational Sectorisation based on Deterministic and Stochastic Partitioning Algorithms. The Sixth SESAR Innovation Days, Nov 2016, DELFT, Netherlands. ⟨hal-01411350⟩