Date of Award

12-1-2010

Degree Name

Master of Science

Department

Computer Science

First Advisor

Hexmoor, Henry

Abstract

The United States leads the world with more than sixty-one million take-offs and landings annually. Air Traffic Controllers are responsible for nearly sixty-four million domestic operations annually (ALPA, 2007). The majority of incursions, about 60%, occur due to pilot deviation, 20% due to operational error, and vehicle and pedestrian deviation account for the remainder (Young, 2001). With increasing air traffic, runway incursions have been proportionally on the rise. As traffic volume increases, the likelihood of a runway incursion increases. Whereas airport size remains constant, the number of landings and take-offs steadily increases. In this thesis, we focus on ways to mitigate congestion at the airports. The main reason for congestion is due to the widening gap between demand and capacity. We can decrease congestion either by enhancing capacity or by managing demand. Increasing capacity is considered as expensive and beyond our reach because of the following reasons (a) it requires large amounts of land which many airports do not own, (b) a huge amount of money is required for construction, and (c) the amount of time for the entire process of adding the new runway can mean a decade (Harsha, 2009). Therefore, we focus on managing demand. The main concern is to close the gap between demand and capacity by allocating scarce resources (i.e., runway usages) efficiently. This can be referred to as a scarce resource allocation problem, as resource is runway time slots. We will focus mainly on two types of efficient runway allocation techniques: airport combinatorial auctions and runway stable matching. In airport combinational auctions, well-designed auctions take place between airport and airlines for runways slots. Airport managers on behalf of airports act as auctioneers and airlines act as bidders. We propose an application which can implement combinatorial auctions among airlines. In runway stable matching, we propose application of Gale-Shapley algorithm and java based application for finding stable matching between airlines and available airports runway slots based on airline and airport's preferences.

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