Optimized Scheduling for Naval Flight Instructors: Automating the Process with ILP
The final phase of training for Naval aviators of the P-8 Community takes place at a squadron in Jacksonville, Florida. Approximately 65 instructor pilots are responsible for teaching new aviators how to fly the aircraft. Efficiently scheduling these instructors is a complex and time-consuming task, requiring careful consideration of availability, seniority, and personal preferences, while adhering to mandatory operational constraints. This research introduces a Python/Pyomo-based integer linear programming (ILP) model that automates the scheduling for both instructors and civilian contractors. The model optimally assigns instructors to simulators and flights, ensuring compliance with constraints such as mandatory crew rest, workload limits, and slot availability.
This solution uses a Dash application and standalone executable to replace a 5-hour manual process with one that runs in seconds, expanding the scheduling forecasts from 1 day to 1 week. The operational squadron now uses this application on a weekly basis to conduct their scheduling.
