AE 590 Seminar Speaker Max Li: Distributionally Robust Optimization and Applications to Air Traffic Management

Abstract: Ground Delay Programs (GDPs) mitigate air traffic demand-capacity imbalances by holding flights on the ground at their origin airports when the destination airport’s arrival capacity is reduced, thereby limiting costly airborne holding. A central challenge is that day-to-day demand-capacity balancing depends on accurate capacity predictions. In practice, however, these predictions are highly uncertain: forecast errors, operational disruptions, and climate-driven changes in weather severity can induce distributional shifts in capacity outcomes. As a result, policies optimized for a single predicted distribution may perform poorly out of sample.

We address this challenge by developing a distributionally robust framework for the single-airport ground holding problem (dr-SAGHP). We further propose a solution approach that integrates Kelly’s cutting plane method with the integer L-shaped method, applicable more broadly to two-stage distributionally robust integer programs with relatively complete recourse and continuous second-stage decision variables. The approach includes a novel dual bisection and primal recovery procedure that exploits problem structure to efficiently generate the subgradients required by Kelly’s method. In computational experiments, the proposed algorithm achieves up to two orders-of-magnitude speedups relative to directly solving the convex reformulation, while maintaining negligible optimality gaps. Numerical results demonstrate that dr-SAGHP yields substantial out-of-sample improvements under moderate to severe distributional shifts, enhancing the robustness and effectiveness of GDP decision-making under capacity uncertainty.

Bio: 
Max is an Assistant Professor of Aerospace Engineering at the University of Michigan, Ann Arbor. He also has courtesy appointments in Civil and Environmental Engineering as well as Industrial and Operations Engineering. Max received his PhD in Aerospace Engineering from the Massachusetts Institute of Technology in 2021. He received his MSE in Systems Engineering and BSE in Electrical Engineering and Mathematics, both from the University of Pennsylvania, in 2018. Max’s research and teaching interests include air transportation systems, airport and airline operations, Advanced Air Mobility, networked systems, as well as optimization and control. Max is the recipient of the NSF CAREER Award, INFORMS Aviation Applications Section Best PhD Dissertation Prize, the FAA RAISE Award, as well as several best paper awards from national- and international-level conferences.