Enhanced Model for Joint Optimization of Arrival and Departure Strategies and Arrival/Departure Capacity Utilization at Congested Airports

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The paper addresses an important problem in air traffic flow management (TFM) and control: the efficient utilization of airport capacity to provide optimal arrival/departure strategies for TFM decision making during periods of congestion. This problem plays a significant role in both FAA’s Next Generation Air Transportation System (NextGen) Airport Program and Single European Sky ATM Research (SESAR) Total Airport Management (TAM) Program, especially in development of integrated Arrival and Departure Management (AMAN/DMAN). The problem of optimal joint allocation of arrivals and departures at airports is addressed by optimizing the dynamic tradeoff between arrival and departure capacities in response to the dynamics of predicted traffic demand. The paper presents an important modification of the original optimization model formulated by E. Gilbo in his 1993 paper. First, we replace the Integer Programming (IP) formulation with a discrete combinatorial optimization version that has both computational and practical advantages. Second, unlike the original optimization model, which is entirely based on aggregate demand counts, this paper further enhances the model by considering individual flights within demand counts and using their predicted arrival and departure times in the optimization procedure. These data add very important practical elements in the optimization model, such as considering available slots, allocating slots to individual flights and the possibility for using various slot assignment rules compatible with the existing Collaborative Decision Making (CDM) procedures. Using these data in the optimization models affects the optimal solutions and adds flexibility in formulating constraints to make the solutions more realistic and acceptable to TFM specialists. Numerical examples for LaGuardia International Airport illustrate advantages of combining aggregate demand and individual flights’ timing predictions for improving strategic arrival/departure traffic management by controlling airport operational resources.