Dynamic Flow Management Problems in Air Transportation

In 1995 over six hundred thousand licensed pilots flew nearly thirty-five million flights into over eighteen thousand U.S. airports logging more than 519 billion passenger miles. Since demand for air travel has increased by more than 50% in the last decade while capacity has stagnated congestion is a problem of undeniable practical significance. In this thesis we will develop optimization techniques that reduce the impact of congestion on the national airspace. We start by determining the optimal release times for flights into the airspace and the optimal speed adjustment while airborne taking into account the capacitated airspace. This is called the Air Traffic Flow Management Problem (TFMP). We address the complexity showing that it is NP-hard. We build an integer programming formulation that is quite strong as some of the proposed inequalities are facet defining for the convex hull of solutions. For practical problems the solutions of the LP relaxation of the TFMP are very often integral. In essence we reduce the problem to efficiently solving large scale linear programming problems. Thus the computation times are reasonably small for large scale practical problems involving thousands of flights. Next we address the problem of determining how to reroute aircraft in the airspace system when faced with dynamically changing weather conditions. This is called the Air Traffic Flow Management Rerouting Problem (TFMRP) We present an integrated mathematical programming approach for the TFMRP which utilizes several methodologies in order to minimize delay costs. In order to address the high dimensionality we present an aggregate model in which we formulate the TFMRP as a multicommodity integer dynamic network flow problem with certain side constraints. Using Lagrangian relaxation we generate aggregate flows that are decomposed into a collection of flight paths using a randomized rounding heuristic.