Use of Decision Analysis in the Army Base Realignment and Closure (BRAC) 2005 Military Value Analysis

Paul L. Ewing (), William Tarantino () and Gregory S. Parnell ()
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Paul L. Ewing: Operations Research Department, Naval Postgraduate School, Monterey, California 93940
William Tarantino: Graduate School of Operational and Information Sciences, Naval Postgraduate School, Monterey, California 93940
Gregory S. Parnell: Department of Systems Engineering, United States Military Academy, West Point, New York 10996-1779

Decision Analysis, 2006, vol. 3, issue 1, 33-49

Abstract: In 2001, Congress enacted legislation that required a 2005 Base Realignment and Closure (BRAC) round to realign military units, remove excess facility capacity, and support defense transformation. The United States Army used multiple-objective decision analysis to determine the military value of installations and an installation portfolio model to develop the starting point to identify potential unit realignments and base closures, providing the basis for all recommendations. Ninety-five percent of the army’s recommendations were accepted by the BRAC 2005 Commission. The army expects these recommendations to create recurring savings of $1.5 billion annually after completion of BRAC implementation. This paper offers four contributions to decision analysis literature: an instructive application of multiple-objective decision analysis methods to portfolio selection, a useful method for constructing scales for interdependent attributes, a new method for assessing weights that explicitly considers importance and variation (Swing Weight Matrix), and practical advice on how to use multiple-objective decision analysis methods in a complex and controversial political environment.

Keywords: decision analysis; BRAC; army; military value; Swing Weight Matrix; portfolio analysis (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (32)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ordeca:v:3:y:2006:i:1:p:33-49

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