Efficient capacity allocation in a collaborative air transportation system

Abstract

This thesis proposes methods of allocating airport capacity to the users of the National Airspace System (NAS) during periods in which demand for the resources exceeds capacity. A metric by which the proposed methods are judged is the value that the users of the N AS are able to realize through the allocation. Maximization of this metric produces notably different results from minimization of flight-minutes of delay and similar objectives employed in related works. The heart of this approach is the treatment of the Federal Aviation Administration (FAA) and the NAS users as solvers of subproblems in a decomposition of the overall problem of determining how to operate the system. The best possible capacity allocation method would allow the users, to achieve the same result collectively that a single omniscient entity in control of all decisions in the system could achieve. The typical approach to decomposition employed in optimization, that of modifying the subproblem objectives through a penalty function determined by a master "dual" problem, is employed in the Objective-Based Allocation Method (OBAM). It is shown that the proper choice of penalty function results in a method that performs well dynamically and, assuming each user operates to maximize its operating objectives through the allocation, achieves the optimal solution that an omniscient single controller would achieve. OBAM requires complete communication of user objectives and constraints to achieve optimality. It also requires that the penalty functions used to coordinate the subproblem solutions be added to the user objective functions through assessment of fees. The second part of this thesis addresses the improvement of the decomposition by changing the nature of the allocation without these requirements. Rather than allocate airport arrival capacity alone, a more general notion of airport capacity that captures the interactions between arrival and departure processes at an airport is allocated. This allows the users the flexibility to adjust the operations mix of the airport according to their objectives and improves the ability of the system to match demand to forecast airport capacity. Through simulation, it is shown that this approach could improve significantly on the primary metric of achieving user value. In addition, the approach facilitates side benefits, such as the reduction of fuel consumption, the reduction of harmful emissions into the environment, and the improvement of service reliability for the flying public.