Optimizing Key Parameters of Ground Delay Program with Uncertain Airport Capacity

The Ground Delay Program (GDP) relies heavily on the capacity of the subject airport, which, due to its uncertainty, adds to the difficulty and suboptimality of GDP operation. This paper proposes a framework for the joint optimization of GDP key parameters including file time, end time, and distance. These parameters are articulated and incorporated in a GDP model, based on which an optimization problem is proposed and solved under uncertain airport capacity. Unlike existing literature, this paper explicitly calculates the optimal GDP file time, which could significantly reduce the delay times as shown in our numerical study. We also propose a joint GDP end-time-and-distance model solved with genetic algorithm. The optimization problem takes into account the GDP operational efficiency, airline and flight equity, and Air Traffic Control (ATC) risks. A simulation study with real-world data is undertaken to demonstrate the advantage of the proposed framework. It is shown that, in comparison with the current GDP in operation, the proposed solution reduces the total delay time, unnecessary ground delay, and unnecessary ground delay flights by 14.7%, 50.8%, and 48.3%, respectively. The proposed GDP strategy has the potential to effectively reduce the overall delay while maintaining the ATC safety risk within an acceptable level.

Understanding the Trade-Off Between Maximum Passenger Throughput and Airline Equity in Allocating Capacity Under Severe Weather Conditions

When the capacity at an airport is reduced because of weather conditions, a ground delay program (GDP) is implemented to resolve the discrepancy between demand for arrival slots and the available arrival slots on a given day. GDPs currently ration the available arrival slots via the proportion of arrivals that exist in the schedule by airline (this practice is termed ration by schedule) with an emphasis on equity among the airlines. Existing rationing schemes do not explicitly consider the number of passengers delayed. This study examined the passenger impacts of a focus on seat throughput in reduced capacity conditions for a GDP at a single airport with consideration for airline equity. An optimization model was developed by using the number of seats available in an aircraft as a proxy for number of passengers and an equity term to estimate airline equity implications. A comparison of the current GDP rationing scheme with one focused on seat delay showed that with no change in the total flight delay time periods, passenger throughput could be improved with a threshold placed on equity. The trade-off between airline equity and passenger throughput and the implications of these results are discussed.