Forecasting air base operability in a hostile environment: Estimating metamodels from large-scale simulations
Abstract
An on-going Air Force logistics concern is the ability of an Air Force unit to fly aircraft into combat particularly when their air base comes under attack. Air bases are no longer sanctuaries; Air Force units must not only survive attacks but continue to operate afterwards as well. Limited budgets and long procurement and training pipelines magnify the problem, making it imperative to specifically identify and resolve support system deficiencies. A systems view of the support structure rather than narrow functional views is essential. We propose a simulation approach to the problem which attempts to capture the logistics infrastructure for a single air base. Multiple simulation runs are used to derive a simpler metamodel useful for forecasting future performance or for evaluating policy alternatives. This metamodel can then be used in lieu of complex and costly simulation models to explore "what if" analyses. Major research issues include the estimation of metamodels from large-scale simulation models with highly correlated responses, experimental design with simular responses and application of variance reduction techniques to large-scale simulation problems. Good variance reduction results are obtained using a classical two-level experimental design with blocking within the fraction based on common random numbers. Two cases, with and without attacks on the air base, are modeled as sub-experiments. Results indicate homogeneity of variance within each case, but heterogeneity between the two cases. A significant difference in the number of sorties flown when the air base is attacked is evident, but this difference dissipates by Day 30. The estimated metamodels indicate that two-way interactions are extremely important and should not be ignored. Also the daily metamodels differ not only in the slopes of the factors, but also in the very factors found to be significant. Many interesting insights into the complexities and interdependencies of the factors defining the logistics infrastructure are highlighted in this research.
Degree
Ph.D.
Advisors
Wilson, Purdue University.
Subject Area
Industrial engineering
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