Preference-based 3-dimensional en-route airspace sectorization.

The problem of 3-Dimensional en-route airspace sectorization has been modelled as a multi-objective optimization by taking into account of conflicting air traffic controller workloads. In practice, air traffic controllers impose limits on these objectives, which may not be captured completely in Pareto front obtained using the multi-objective model. Hence, in this paper, we propose a preference-based multi-objective optimization model for 3-dimensional en-route sectorization. Through the use of reference point(s), the proposed model is able to find multiple solutions that satisfy the air traffic controller preference(s) faster. Population-based NSGA-II has been used to solve the preference-based 3-dimensional en-route sectorization problem. The performance of preference based sectorization is evaluated using actual flight data from the Singapore regional airspace. The results are compared with conventional multi-objective optimization model which integrates the preference as a constraint. Results indicate that the preference-based model generally performs better than the constraint-based model. Further, multiple parallel runs of preference-based optimization could provide a greater variety of choices in airspace sectorization for the air traffic controllers.