Strategic Planning in Air Traffic Control as a Multi-objective
  Stochastic Optimization Problem
  With the objective of handling the airspace sector congestion subject to
continuously growing air traffic, we suggest to create a collaborative working
plan during the strategic phase of air traffic control. The plan obtained via a
new decision support tool presented in this article consists in a schedule for
controllers, which specifies time of overflight on the different waypoints of
the flight plans. In order to do it, we believe that the decision-support tool
shall model directly the uncertainty at a trajectory level in order to
propagate the uncertainty to the sector level. Then, the probability of
congestion for any sector in the airspace can be computed. Since air traffic
regulations and sector congestion are antagonist, we designed and implemented a
multi-objective optimization algorithm for determining the best trade-off
between these two criteria. The solution comes up as a set of alternatives for
the multi-sector planner where the severity of the congestion cost is
adjustable. In this paper, the Non-dominated Sorting Genetic Algorithm
(NSGA-II) was used to solve an artificial benchmark problem involving 24
aircraft and 11 sectors, and is able to provide a good approximation of the
Pareto front.
