An optimization model to fit airspace demand considering a spatio-temporal analysis of airspace capacity

The European and U.S. airspace systems are highly congested at certain peak time intervals. Controllers' workloads have reached generally accepted limits; therefore, many highly demanded sectors are subject to traffic regulations and restrictions during many hours of each day. A lack of a spatio-temporal analysis of the airside capacity management tools generates airside delays at the destination airport in the form of holding or path-stretching in terminal manoeuvring areas, or even during the cruise by re-routing. These emergent dynamics are demonstrated every day by the urgent need for new and better tools for analyzing and making strategic and tactical decisions that neither induce delays nor negatively impact daily operations. This paper presents an optimization model for airspace capacity-demand management that performs an efficient departure time bounded adjustment configuration for trajectory based operations. This optimization model is supported by the 4D trajectories paradigm, in which a discrete event model has been developed to formalize the trajectories' spatio-temporal interdependencies. Based on the elements and parameters declared on the validated coloured Petri net model, a set of constraints is obtained. By means of constraint programming, feasible solutions for demand-capacity imbalances are proposed for a case study scenario, while the original departure slots are preserved in addition to the airspace users' preferences. The results obtained show the advantages in terms of capacity and robustness that can be achieved by applying an efficient departure time bounded adjustment configuration. (C) 2015 Elsevier Ltd. All rights reserved.