A Combined Adaptive Tabu Search and Set Partitioning Approach for the Crew Scheduling Problem with an Air Tanker Crew Application

Aerial refueling is a crucial component of modern day military operations. A vital part of this refueling process is the individual tanker crews. Constrained by the number of tanker crews available, the United States Air Force must find ways to efficiently schedule them. This research develops two effective tabu search approaches to Air Mobility Command's tanker crew scheduling problem. The first is an adaptive tabu search with intensification. The second is a hybrid adaptive tabu search/set partitioning scheme that combines the metaheuristic tabu search with a classical optimization approach.