IMPROVING AUTOMATED SCHEDULES FOR NAVAL AIR STATION KINGSVILLE
Ye, Jasmine L.
Dell, Robert F.
Craparo, Emily M.
Hyink, Jeffrey F.
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Currently, many squadrons in the Naval Aviation community handwrite their daily flight schedules, which is typically an all-day effort. This thesis creates an optimization model to build schedules computationally instead of manually for Navy’s Training Squadron 22 (VT-22), which specializes in Intermediate Jet and Advanced Strike training. An optimized scheduling process can improve the efficiency of the training pipeline, saving money and improving aviation readiness. A preliminary model, Training Event Scheduling Tool (TEST), was provided to VT-22 in 2019 by Meditz. TEST takes a spreadsheet containing student prerequisites, instructors, and events, and creates a daily or weekly schedule at an hourly resolution. This thesis formulates and tests a revised integer linear program, TEST-2, an enhancement to TEST that models weather, substitutable events, and student currency. TEST-2 creates daily schedules in less than 10 minutes and weekly schedules in about four hours. These schedules consider a majority of the necessary constraints for a useable schedule. For a sample week’s input provided by VT-22, TEST-2 schedules about 60 more events over the course of the week than were manually scheduled and completed. Currently, many events are cancelled due to instructor non-availabilities, weather, and jet availability. Because TEST-2 considers these three factors in building its schedules, cancellations due to these factors are minimized.
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