Stochastic preemptive goal programming of Air Force weapon systems mix
We demonstrate a new approach to conducting a military force structure study under uncertainty. We apply the stochastic preemptive goal program approach, described by Ledwith et al., to balance probabilistic goals for military force effectiveness and the force’s cost. We use the Bayesian Enterprise...
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Published in: | Journal of defense modeling and simulation Vol. 20; no. 2; pp. 147 - 158 |
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Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
London, England
SAGE Publications
01-04-2023
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Subjects: | |
Online Access: | Get full text |
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Summary: | We demonstrate a new approach to conducting a military force structure study under uncertainty. We apply the stochastic preemptive goal program approach, described by Ledwith et al., to balance probabilistic goals for military force effectiveness and the force’s cost. We use the Bayesian Enterprise Analytic Model (BEAM), as described in “Probabilistic Analysis of Complex Combat Scenarios,” to evaluate effectiveness, expressed in terms of the probability of achieving campaign objectives, in three hypothetical scenarios. We develop cost estimates along with their uncertainty to evaluate the force’s research and development, production, and annual operating and support costs. Our summary depicts how the trade-off between various prioritized goals influences the recommended robust force. Our approach enables defense leaders to balance risk in both force effectiveness in various scenarios along with risk in different types of cost categories. |
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ISSN: | 1548-5129 1557-380X |
DOI: | 10.1177/15485129211051751 |