This dissertation details an algorithm to solve the Intratheater Airlift Operations Problem (IAOP) using advanced tabu search. A solution to the IAOP determines the routes and assignment of customer requests to a fleet of aircraft over a given time horizon. This problem and other variants comprise an ongoing challenge for United States Air Force (USAF) planners who manage detailed logistics throughout many theaters of operations. Attributes of the IAOP include cargo time windows, multiple cargo types, multiple vehicle cargo bay configurations, vehicle capacity, route duration limits, and port capacities. The IAOP multi-criteria objective embraces several components with the primary goal of satisfying as much of the demand as possible while minimizing cost. The algorithm is extended to allow split load deliveries of customer requests, allowing a shipment to be split into two or more sub-loads which are delivered separately to the customer. The split load relaxation, while significantly increasing the complexity of the problem, allows for possible improvement in the solution. The necessary changes to the model and algorithm are detailed, providing a foundation to extend any local search algorithm solving a vehicle routing problem to allow split loading. Results allowing split loading are presented and compared with results without split loading. The algorithm is also extended to include a rolling time horizon. Starting from a solution found at a previous time step, the algorithm is limited on how the solution can be modified. This reflects the reality of operations in which near-term plans are locked as they approach and enter execution while longer-term plans are continually updated as new information arrives. / text