Optimization of NAS Lemoore scheduling to support a growing aircraft population

Abstract

The current manual process for aircraft flight scheduling at Naval Air Station (NAS) Lemoore accommodates the independent needs of 16 fighter resident squadrons as well as constraints imposed by limited military operating area (MOA) availability. Given the complexity of this scheduling problem, attempting to additionally avoid periods of high activity, which lead to congestion, would challenge the manual process. Congestion leads to long wait times for flight-line services. Refueling operations are particularly costly when operational time is lost and resources are backlogged. Avoiding inefficient periods of high demand for refueling operations is complicated by the two types of refueling available: hot refueling when the aircraft's engine is running or cold refueling when the aircraft is shut down. Although cold refueling is more fuel efficient, it is also more time consuming. Scheduling aircraft to avoid inefficient periods of high demand and achieving a balance between the two refueling methods are keys to maximizing the effectiveness of NAS Lemoore operations, particularly as Lemoore's aircraft population will grow in the coming years. This thesis creates an optimization model to determine the best daily flight schedules based on current NAS Lemoore squadrons, the squadrons' flying and training requirements, the refueling infrastructure, and MOA availability. It also exercises the model to study the impact of the growing aircraft population estimated for 2017 and 2018.