Due the remarkable growth in the size and complexity of airlift operations, there is an increased need for planning tools to assist decision makers with issues ranging from selecting the number and types of aircraft for an airlift fleet to making informed decisions with respect to investing or divesting in overseas air bases. In Fiscal Year (FY) 94 research was initiated in the Operations Research Department of the Naval Postgraduate School in response to a request from the United States Air Force Studies and Analyses Agency and resulted in the development of a high fidelity strategic airlift optimization model called Throughput II. The model is formulated as a multi-period, multi-commodity linear programming model for determining the maximum on-time throughput of cargo and passengers that can be transported with a given fleet or given network, subject to appropriate physical and policy constraints. Troop and equipment movement requirements are specified by the Time Phase Force Deployment Data (TPFDD). An optimization model that utilizes the full level of detail available in a TPFDD would be of intractable size. Moreover, it is not necessary to build a model with such a fine level of detail in order to obtain the important insights required to assist decision makers. Therefore Throughput II replaces the potentially large set of airfields with a smaller set of centroids and schedules aircraft through these aggregated airfields. Currently route selection is performed manually, by an expert, who incorporates a variety of factors based on his/her experience. In this thesis we develop techniques for selecting a set of candidate routes for any deployment scenario without requiring historical data or extensive interaction with an expert. An analyst should be concerned about two potentially detrimental effects of these preprocessing procedures.