Airports often operate under tight gate availability while facing highly uncertain flight arrival times, leading to cascading delays, passenger misconnections, and inefficient resource utilization. This paper presents a mixed-integer optimization model for the airport gate assignment and turnaround scheduling problem that explicitly accounts for delay propagation, passenger connectivity, and operational trade-offs. The proposed model simultaneously determines gate assignments, flight sequencing, and turnaround buffer schedules in order to minimize total system disruption, including flight delays, passenger walking distances, and missed connections. Several operational scenarios are analyzed to evaluate the model under varying conditions, including tight passenger connections, gate blocking events, and trade-offs between passenger convenience and delay costs. Sensitivity analyses demonstrate the robustness of the proposed model under different economic cost configurations while highlighting its ability to capture operational disruptions and delay propagation effects. Managerial insights highlight how airports and airlines can use such models to improve punctuality, passenger experience, and operational resilience. The findings suggest that integrating scenario-based evaluation into gate assignment decisions can substantially enhance airport performance in congested and uncertain operating environments.

Keywords

Gate Assignment, Turnaround Scheduling, Operations Research, Mixed-Integer Programming, Airport Operations.