This work addresses the real-time problem of managing take-off and landing operations in presence oftraffic disturbances at a busy Terminal Control Area (TCA). An important objective of traffic controllers isthe minimization of delay propagation, which may reduce the aircraft travel time and the energyconsumption. To improve the effectiveness of air traffic monitoring and control in a busy TCA, we presentan advanced optimization-based decision support system and compare centralized and rolling horizonapproaches. The possible aircraft conflict detection and resolution actions are viewed as aircraft timing androuting decisions. The problem is modeled via an alternative graph formulation, i.e. a detailed model of airtraffic flows in the TCA, and solved by scheduling and re-routing algorithms. We also propose a new MILPformulation in order to compute (near)optimal scheduling and routing solutions. We compare the first infirst out rule, used as a surrogate for the dispatchers behavior, a truncated branch and bound algorithm foraircraft scheduling with fixed routes, a tabu search algorithm for combined aircraft scheduling and rerouting,and the MILP formulation solved via a commercial solver. Computational experiments arepresented for practical-size instances from Milano Malpensa airport. Disturbed traffic situations aregenerated by simulating various sets of delayed landing/departing aircraft. A detailed analysis of theexperimental results demonstrates that the solutions produced by the optimization algorithms are of aremarkable better quality compared to FIFO, in terms of delay and travel time minimization.
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