A Multi-Objective Approach For 3d Airspace Sectorization: A Study On Singapore Regional Airspace

This paper presents an automatic airspace sectorization method for air traffic management in presence of many climbing trajectories. For this purpose, we have modified the formulation, and solved it using Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Voronoi diagrams. The air traffic controller's monitoring workload is formulated with the use of modified dynamic density, which is a more rigorous and accurate formulation as compared to the simplistic metrics used in other works. The multi-objective formulation is implemented using historical flight data within Singapore regional airspace. The results clearly indicate that the en-route 3D sectorization using dynamic density in monitoring workload formulation provides better workload balance in ATC compared to 2D sectorization.