%0 Conference Paper %F Oral %T 3D Sectors Design by Genetic Algorithm Towards Automated Sectorisation %+ ENAC - Laboratoire de Mathématiques Appliquées, Informatique et Automatique pour l'Aérien (MAIAA) %+ Ecole Nationale de l'Aviation Civile (ENAC) %+ Eurocontrol %A Sergeeva, Marina %A Delahaye, Daniel %A Mancel, Catherine %A Zerrouki, Leila %A Schede, Nick %< avec comité de lecture %B SID 2015, 5th SESAR Innovation days %C Bologna, Italy %8 2015-12-01 %D 2015 %K genetic algorithm %K k-means clustering %K esctor design %Z Mathematics [math]/Optimization and Control [math.OC]Conference papers %X The aim of this work is to develop a research prototype to support the validation of new airspace sector design methodology. To do this, an algorithm has been developed that manages main features of the sector design process. The proposed method is based on a mathematical modeling and heuristic optimization techniques. In order to run this algorithm efficiently a pre-processing step has been proposed, which creates an initial division of the airspace into Voronoi cells using k-means clustering algorithm. Then, due to the induced combinatorial complexity, a stochastic optimization algorithm based on artificial evolution has been applied to solve the sectorisation problem. An evaluation of the algorithm is presented as well, with a comparison to existing sectorisation with the support of the operational expertise. %G English %2 https://enac.hal.science/hal-01240312/document %2 https://enac.hal.science/hal-01240312/file/SIDs_2015_paper_37.pdf %L hal-01240312 %U https://enac.hal.science/hal-01240312 %~ ENAC %~ INSMI %~ MAIAA %~ MAIAA-OPTIM %~ TDS-MACS %~ OPTIM