© 2013 Dr. Sophie Kenrick Dickson ; Airline scheduling is traditionally concerned with developing a plan that is most profitable, and is usually done under conditions that are assumed to be known. In reality, however, airline operations are subject to uncertainty such as weather, traffic and equipment failure which cause disruption to passengers. In this thesis, we explore ways to design schedules that are robust to disruption as well as approaches for recovering once disruption has occurred. We formulate these problems as Integer Programming models. Most of these models are difficult to solve and require specialised IP solution approaches to solve them in a reasonable time frame. For both the robust schedule design and recovery problems, computational results are presented to explore the computational efficiency of the solution approaches developed, as well as results demonstrating the quality of the solutions obtained. Using the robust schedule design methodology developed, we analyse the resulting schedules to generate insights into where slack time is best allocated to maximise its effectiveness. For both problems, we also investigate the underlying structure of the Integer Programs to understand the conditions under which an integer valued optimum will be obtained when solving the linear relaxation. The thesis consists of two main components: Part II which presents our approach to solving the robust airline scheduling problem and Part III which presents our approach for solving the recovery problem. The remaining parts, I and IV, form the introduction and conclusion to the work, providing the motivation for the work contained within the thesis and drawing the links between Parts II and Part III.