The runway sequencing problem : optimizing congested runways

Abstract

During the past two decades, air travel has witnessed a rapid increase with airports being burdened with the ultimate problem of runway congestion. Consequently, manual runway sequencing has become unsustainable for regularly busy airports. The problem of determining the order in which aircraft use a runway, the Runway Sequencing Problem, has become complex more than ever, instigating the need for airports to implement more efficient runway sequencing techniques. Developing a system which air traffic controllers can use to solve the sequencing task within a significantly short time, overall increases the airport's efficacy. The aim of this dissertation is to study methods through which aircraft take-offs can be sequenced intelligently so as to improve the runway throughput. We formulate this problem as a mathematical model and propose exact and metaheuristic techniques, namely the Branch & Cut and Genetic algorithms, to produce take-off schedules. The results in this study illustrate the effectiveness of a non-First-Come First-Serve schedule over a First-Come First-Serve one. Moreover, the findings attained illustrate high-quality and efficient sequences that are viable to real-world instances, like the ones considered throughout this study.