Auction-Based Slot Allocation for Traffic Demand Management at Hartsfield Atlanta International Airport: A Case Study

Abstract

Ongoing research is described for an auction model, a hybrid demand management approach for congested airports. This approach is intended to optimize the use of airport time slots by maximizing passenger throughput with safe capacity, decreasing congestion, and less delay. The two submodels mathematically formulate conflicting optimization problems of efficiency-driven airport regulators and cost-driven airlines. By ranking key factors such as monetary bidding, flight origin-destination pairs, enplanement capability, and airlines' previous investments, a framework is presented that is open to many design alternatives. Two design alternatives are analyzed in a case study of Hartsfield Atlanta International Airport, Georgia, to compare different allocation schemata and resulting airport performance. The performance analysis used a queuing model simulation. By varying weighting coefficients for bid vectors, it is proposed that the effects of administrative coordination and market force on outcomes of the auction process could be monitored to achieve airport-specific benefits. It is also suggested that the conventional auction format that uses monetary bidding alone could lead to potential distortions of the marketplace and fail to meet air transportation officials' concerns about the efficient use of national resources and policy makers' concerns about market structure and competitiveness. Future work will enlist the input from both airlines and airports.