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Most flight delays are created by imbalances between demand and capacity at the busiest airports. Absent large increases in capacity, airport congestion can only be mitigated through scheduling interventions or improved capacity utilization. This paper presents an integrated approach that jointly optimizes the airport’s flight schedule at the strategic level and the utilization of airport capacity at the tactical level, subject to scheduling, capacity, and delay-reduction constraints. The capacity-utilization part involves controlling the runway configuration and the balance of arrival and departure service rates to minimize congestion costs. The schedule optimization reschedules a selected set of flights to reduce the demand-capacity mismatches while minimizing interference with airline competitive scheduling. We develop an original iterative solution algorithm that integrates a stochastic queuing model of airport congestion, a dynamic programming model of capacity utilization, and an integer programming model of scheduling interventions. The algorithm is shown to converge in reasonable computational times. Extensive computational results for JFK Airport suggest that substantial delay reductions can be achieved through limited changes in airline schedules. It is also shown that the proposed integrated approach to airport congestion mitigation performs significantly better than the typical sequential approach, where scheduling and operational decisions are made separately.
Jacquillat et al. (Tue,) studied this question.