Schedule disruptions commonly affect airline operations and cause a great disparity between the expected and actual operational costs. As such, there is much interest in developing planning methods that avoid these schedule disruptions. One such method is recoverable robustness. A recoverable robust problem is solved to identify planning solutions that require little work to return operations back to plan in the event of flight delays or cancellations. The key feature of recoverable robustness is that the planning and recovery aircraft routing problems are solved simultaneously in the solution process. The resulting problem formulation is in the form of a stochastic program. Hence, a variety of sophisticated solution approaches, such as Benders' decomposition and column generation, are required to reduce the runtimes required to identify the optimal solution. This talk will introduce the concept of recoverable robustness and discuss its application to aircraft routing problems. In addition, the various solution techniques employed for this problem will be discussed.