We study the practical setting in which regular- and reserve-crew schedules
are dynamically maintained up to the day of executing the schedule. At each day
preceding the execution of the schedule, disruptions occur due to sudden
unavailability of personnel, making the planned regular and reserve-crew
schedules infeasible for its execution day. This paper studies the fundamental
question how to repair the schedules' infeasibility in the days preceding the
execution, taking into account labor regulations. We propose a robust repair
strategy that maintains flexibility in order to cope with additional future
disruptions. The flexibility in reserve-crew usage is explicitly considered
through evaluating the expected shortfall of the reserve-crew schedule based on
a Markov chain formulation. The core of our approach relies on iteratively
solving a set-covering formulation, which we call the Robust Crew Recovery
Problem, which encapsulates this flexibility notion for reserve crew usage. A
tailored branch-and-price algorithm is developed for solving the Robust Crew
Recovery Problem to optimality. The corresponding pricing problem is
efficiently solved by a newly developed pulse algorithm. Based on actual data
from a medium-sized hub-and-spoke airline, we show that embracing our approach
leads to fewer flight cancellations and fewer last-minute alterations, compared
to repairing disrupted schedules without considering our robust measure