Feasibility Study of Variance Reductionin the THUNDER Campaign-Level Model
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As an Air Force Chief of Staff endorsed topic, Air Force Studies and Analyses Agency (AFSAA) requested an effective and efficient way to reduce the variance in analysis results from THUNDER. THUNDER is a large-scale discrete event simulation of campaign-level military operations and is used to examine issues involving the utility and effectiveness of air and space power in a theater-level, joint warfare context. Given the large number of stochastic components within THUNDER, results are produced with highly variable measures of effectiveness (MOEs), causing difficulties in evaluating alternati...
As an Air Force Chief of Staff endorsed topic, Air Force Studies and Analyses Agency (AFSAA) requested an effective and efficient way to reduce the variance in analysis results from THUNDER. THUNDER is a large-scale discrete event simulation of campaign-level military operations and is used to examine issues involving the utility and effectiveness of air and space power in a theater-level, joint warfare context. Given the large number of stochastic components within THUNDER, results are produced with highly variable measures of effectiveness (MOEs), causing difficulties in evaluating alternative force structures, weapon systems, etc. This work responds to AFSAA's request by examining the application of Common Random Numbers (CRN), Antithetic Variates (AV), Control Variates (CV), and a combination of AVs and CVs and a combination of CRNs and CVs.
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