A new solution approach to airspace sectorization problem

As a result of the rapid development of the air transportation in recent years, the delays and congestion give rise to insufficient capacity in the Air Traffic Management System in many countries all over the world. In line with this, studies conducted in order to strike the capacity-demand balance became more important. Hence, the need for sectorization studies that would provide a more balanced distribution of the air traffic density has increased. Because of the dynamic structure of air transportation and the dependence of air traffic controller workload on many parameters and variables, the airspace sectorization is among the difficult and complicated problems.In this study, through the analytical modeling approach which takes into account both the workload of air traffic controller and the complexity of the airspace which are the most important parts of the air traffic system, bringing a new dimension to the airspace sectorization problems has been aimed. In this context, a grid based method has been used in order to distribute evenly the air traffic controller workload to sectors. In order to balance the workload of the sectors, a multi-objective mixed integer optimization model has been developed.In the first step of this PhD dissertation study, an airspace analysis tool has been developed by using Geographical Information Systems (GIS), and the Turkish Airspace, chosen as an application, has been divided into 471 parts of 0.5° separation and of equal areas by using a square grid. In the second step, an Airspace Workload Measurement Model has been developed in order to measure the workloads of each square unit and the workload of the total airspace. In the final step of the study, a model for optimum airspace sectorization based on the controller workload has been developed by using optimization theory and clustering algorithm in order to realize sector boundary determination.