Date of Award

3-2005

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Operational Sciences

First Advisor

Kenneth W. Bauer, PhD

Abstract

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. The difference between the standard output and variance reduced output halfwidths for 95% confidence intervals were examined. Analysis of the correlation between MOEs and the random inputs in the CV technique provided insight into the workings of THUNDER. A new, state of the art combined multiple recursive generator was incorporated into THUNDER to synchronize the random inputs for CRN and AV. The result is methodology for implementing all four variance reduction techniques.

AFIT Designator

AFIT-GOR-ENS-05-01

DTIC Accession Number

ADA441639

Download

Share

COinS