Mathematical Models And Algorithmic Solution Approaches For The Slot Allocation Problem

At busy airports, the long-term strategic planning of air traffic is achieved through the allocation of slots. These slots govern which flights arrive and depart at an airport during a particular time, allowing an aircraft to use scarce infrastructure such as runways. The complex decision-making process in the allocation of slots, an increased forecast in air traffic demand and shift in policy towards short-medium term airport capacity expansion plans has driven the need for increased research with the aim of improving efficiency in the slot allocation process. This thesis aims to enhance decision making processes and research for the single airport and network level slot allocation problem. A number of novel models are developed to better capture aspects within slot allocation that can lead to improvements in schedule efficiency. These models capture and enhance a number of aspects such as rejected requests, flexibility, seasonality and network considerations. In addition, heuristic solution approaches are developed in order to tackle the complex problems considered. Furthermore, this thesis aims to contribute to the enrichment of slot allocation data for the research community to better facilitate the development and testing of solution methods. This thesis makes the following contributions to knowledge by a) improving the available data sets to be used within slot allocation research at the single airport and network level; b) developing a hyper-heuristic approach to increase the generality in constructing schedules; c) considering seasonal flexibility in the slot allocation problem through the use of a Late Acceptance Hill-Climbing algorithm; d) a matheuristic approach for the network slot allocation problem; e) investigating schedule quality when solving the slot allocation problem at the single airport level or network level.