  Limiting flight delays during operations has become a critical research topic
in recent years due to their prohibitive impact on airlines, airports, and
passengers. A popular strategy for addressing this problem considers the
uncertainty of day-of-operations delays and adjusts flight schedules to
accommodate them in the planning stage. In this work, we present a stochastic
programming model to account for uncertain future delays by adding buffers to
flight turnaround times in a controlled manner. Specifically, our model adds
slack to flight connection times with the objective of minimizing the expected
value of the total propagated flight delay in a schedule. We also present a
concurrent solution framework that integrates an outer approximation
decomposition method and column generation. Further, we demonstrate the
scalability of our approach and its effectiveness in reducing delays with an
extensive simulation study of five different flight networks using real-world
data.
