Each year, the United States Army recruits and trains thousands of soldiers to fill vacancies in Army organizations. Installations responsible for training new recruits are scattered across the United States. Initial entry training for new recruits is conducted in two phases: basic combat training (BCT) followed by advanced individual training (AIT). In this paper we present the following: (1) a mathematical dynamic model of BCT; (2) a decision model for optimally scheduling training resources based on dynamic programming; and (3) an improved automated heuristic procedure for scheduling training resources that incorporates a "training quality" performance measure into the formulation of the objective function, making it possible to compare competing feasible training schedules obtained by various methods. Computational experiments reveal that the heuristic procedures developed are indeed computationally efficient and provide "good" solutions in terms of training "quality", resource utilization; and training cost.
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