Maximizing Robustness of Aircraft Routing with Heterogeneous Maintenance Tasks

In aircraft maintenance routing, the disruption caused by the stochasticity of the maintenance duration is a critical challenge. Previous studies considered the sources of disruptions in an aggregated manner, which resulted in aircraft schedules with insufficient robustness. In this study, we incorporated the uncertainties of heterogeneous maintenance tasks into a robust aircraft routing decision framework and considered other sources of disruptions. Our aim is to study the impact of maintenance task uncertainties on aircraft schedules. Accordingly, we propose a robust aircraft maintenance routing model, which is solved by an accelerated column generation algorithm. Computational experiments are conducted based on actual flight data to examine the efficiency of the proposed algorithm. The results show that the proposed acceleration strategies significantly speeded up the computational process without affecting the solution quality. Moreover, robust aircraft routes were obtained that were less vulnerable to maintenance disruptions.