Scenario-based robust reachability analysis for networked airport delay dynamics.

This work introduces a novel scheme to represent delay dynamics in airport networks. A key feature of the proposed scheme is that uncertainty affecting network operation is accounted for via a robust reachability analysis approach. In particular, the dynamical system is adopted to describe the propagation of outbound and inbound delays between airport nodes. A probabilistic reach set for this networked system is formulated as a chance-constrained optimization program. Then, we resort to a data-driven randomized computation method called $ \it{scenario optimization} $ scenariooptimization , where the chance constraint is replaced by a set of scenario-based deterministic constraints. Besides, the robustness of the reach set is explicitly derived through a posterior algorithm. Moreover, we conduct the extensive experiments on a dataset of real-world airport delays in China and provide some interesting results. Additionally, the case study at a refined scenario level shows the potential of the proposed approach in application. [ABSTRACT FROM AUTHOR]