Dynamic Airpace Configurations Generated by Evolutionary Algorithms

Marina Sergeeva (1) , Daniel Delahaye (1) , Leila Zerrouki (2) , Nick Schede (2)

1 MAIAA - ENAC - Laboratoire de Mathématiques Appliquées, Informatique et Automatique pour l'Aérien
2 Eurocontrol

This paper focuses on the process of generating a sequence of sector configurations composed of two airspace component types Sharable Airspace Modules (SAMs) and Sectors Building Blocks (SBBs). An algorithm has been developed that manages the main features of the dynamic sectors configuration (including sector design criteria). In order to make it run efficiently a pre-processing step will be presented to create a graph modelling of the inputs. Based on this initial graph, a mathematical model is defined which can be summarized by a multi-periods geometric graph partitioning problem. State, space, objective function and constraints will be also presented. Due to the induced complexity, a stochastic optimization algorithm based on artificial evolution is then proposed. A two layer chromosome is used for such a genetic algorithm for which recombination operators are proposed. Evaluation of the algorithm will be presented with a comparison to existing tools and operational approach.

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

Marina Sergeeva, Daniel Delahaye, Leila Zerrouki, Nick Schede. Dynamic Airpace Configurations Generated by Evolutionary Algorithms. DASC 2015 IEEE/AIAA 34th Digital Avionics Systems Conference, Sep 2015, Prague, Czech Republic. pp.1F2-1-1F2-15/978-1-4799-8939-3, ⟨10.1109/DASC.2015.7311352⟩. ⟨hal-01224193⟩