Developing Discrete Empirical Distributions for Tractable Stochastic Programming Problems with Application for U.S. Army Force Sizing




Checco, John

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Providing for the common defense of the United States and its interests is a vital, though expensive, endeavor. To that end, the U.S. Army is expected to grow and shrink as necessary to conform to changing circumstances. Current analytic methods focus on operational (combat) requirements in developing resource constrained operational force designs. These tend to rely on simulation of static operational force structures with fixed readiness policies. Additionally, the Army’s primary strategic force structure analysis models have no direct linkage to cost, instead relying on manpower limits. This type of approach is ill-suited to consider the cost vs. benefit tradeoff of the Army, or the overall size and composition of the Army, and how it should adapt over time to changing conditions.



Operations research, Army force size, Army force structure, Discrete Empirical Distribution, Multistage, Stochastic Optimization, Stochastic Programming