https://hal-enac.archives-ouvertes.fr/hal-01224193Sergeeva, MarinaMarinaSergeevaMAIAA - ENAC - Laboratoire de Mathématiques Appliquées, Informatique et Automatique pour l'Aérien - ENAC - Ecole Nationale de l'Aviation CivileDelahaye, DanielDanielDelahayeMAIAA - ENAC - Laboratoire de Mathématiques Appliquées, Informatique et Automatique pour l'Aérien - ENAC - Ecole Nationale de l'Aviation CivileZerrouki, LeilaLeilaZerroukiEurocontrol - EurocontrolSchede, NickNickSchedeEurocontrol - EurocontrolDynamic Airpace Configurations Generated by Evolutionary AlgorithmsHAL CCSD2015[MATH.MATH-OC] Mathematics [math]/Optimization and Control [math.OC]Porte, Laurence2015-11-05 14:38:382021-10-19 11:02:482015-11-09 16:17:39enConference papershttps://hal-enac.archives-ouvertes.fr/hal-01224193/document10.1109/DASC.2015.7311352binary/octet-stream1This 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.