Abstract
We propose, optimize, and validate a methodological framework for estimating the extent of the crew-propagated delays and disruptions (CPDDs). We identify the factors that influence the extent of the CPDDs and incorporate them into a robust crew-scheduling model. We develop a fast heuristic approach for solving the inverse of this robust crew-scheduling problem to generate crew schedules that are similar to real-world crew-scheduling samples. We develop a sequence of exact and heuristic techniques to quickly solve the forward problem within a small optimality gap for network sizes that are among the largest in robust crew-scheduling literature. Computational results using four large real-world airline networks demonstrate that the crew schedules produced by our approach generate propagation patterns similar to those observed in the real world. Extensive out-of-sample validation tests indicate that the parameters calibrated for one network perform reasonably well for other networks. We provide new insights into the perceived trade-off between planned costs and delay costs as reflected by actual airline crew schedules. Finally, we present a general approach to estimate the CPDDs for any given network using our methodological framework under a variety of data availability scenarios. The online appendix is available at https://doi.org/10.1287/trsc.2018.0834 .
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