Delay propagation is a significant driver of flight delay in aviation networks, yet modelling it at a network-wide scale remains challenging. This study investigates to what extent scheduled max-plus linear systems, as used in railway delay modelling, can be applied to aviation networks. Using the Hawaiian Airlines network as a case study, a methodology is developed to model aircraft rotation and passenger transfer precedence relations within a max-plus linear system. The approach enables the calculation of stability indicators such as maximum cycle mean, recovery times, and network slack, as well as the simulation of delay propagation under various initial delay scenarios.

Results show that the recovery matrix is a valuable tool for identifying structurally vulnerable parts of the network and for assessing the impact of holding aircraft for transferring passengers. However, predictive accuracy of delay propagation for individual flights is limited, primarily due to uncertainties in process time estimation and incomplete knowledge of precedence relations. The 24-hour periodicity of aviation timetables, combined with large overnight buffers, further limits multi-day delay propagation modelling. These limitations are partly specific to the case under study and partly inherent to the deterministic, periodic structure of scheduled max-plus systems.

The study concludes that max-plus linear systems can provide meaningful insights into structural robustness and the systemic impact of schedule design choices, but their use for precise short-term delay prediction in aviation is constrained without high-quality operational data. Future work should explore integration of stochastic max-plus models, application to networks with shorter periodicity, and validation using airline-provided operational datasets.