Demand management at congested airports: How far are we from utopia

The aim of this research is to help solve the airport congestion problem. The returned air traffic growth is putting pressure on airport infrastructure. We identify the causes of congestion to include (i) the High-Density-Rule (HDR) with grandfather rights allocating the limited number of airport slots to incumbent carriers, (ii) weight-based landing fees that do not incentivize airlines to use larger aircraft, (iii) slot exemptions granted to small markets served by 70-seat or less aircraft, and (iv) the 80%-use-it-lose-it requirement forcing airlines to fly low load-factor flights. With HDR at New York LaGuardia and John F. Kennedy International airports scheduled to end in January 2007, appropriate demand management measures are critically needed to avoid overscheduling and severe congestion. Conventional economic wisdom suggests that market-based mechanisms such as congestion pricing and auctions are an efficient way to allocate scarce resources. Congestion pricing and auctions have had successful applications in many fields. In air transportation however, the complexity of airline network synergy, the influence of market power, and airport public goals require the understanding of airline operations and market economics to design the right incentives, as well as the understanding of potential implications of market response on metrics of public interest such as enplanement opportunities, average fare, markets served, aircraft size, and flight delay.;Our research demonstrates the existence of profitable flight schedules that maintain or improve the public goals for LaGuardia airport. To find these schedules, we take a novel approach in modeling a profit-seeking, single benevolent airline, and develop an airline flight scheduling and fleet assignment model to simulate scheduling decisions. This airline is defined as benevolent in the sense that the airline reacts to actual price elasticities of demand estimated in a competitive market. Unlike existing flight scheduling models that use fare as a parameter, our approach explicitly accounts for the interaction of demand and supply through price. Extensive data mining of publicly available databases is conducted to estimate cost and price elasticities of demand. On the airport side, airline schedules are selected to maximize enplanement opportunities such that these schedules fit into LaGuardia's IMC rate constraints. To reconcile the two conflicting objective functions, we look at two compromise solutions that maximize the number of seats while ensuring that airlines operate within 90% or 80% of profit optimality.;We conclude that, with airport's runway rate restricted at the Instrument Meteorological Condition (IMC) rate of 8 ops/runway/15 min, there exist profitable flight schedules that have fewer flights and reduce substantially average flight delay while accommodating the current passenger demand at prices consistent with that demand. The IMC rate provides a predictable on-time performance for the identified schedules in all weather conditions. (Abstract shortened by UMI.)...