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A hybrid approach of goal programming for weapon systems selection

Cited 42 time in Web of Science Cited 73 time in Scopus
Authors

Lee, Jaewook; Kang, Suk-Ho; Kim, Seoung Bum; Rosenberger, Jay

Issue Date
2010-04-01
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Citation
COMPUTERS & INDUSTRIAL ENGINEERING; Vol.58 3; 521-527
Keywords
Multiple criteria decision analysisPrincipal component analysisWeapon systemsGoal programmingAnalytic hierarchy process
Abstract
Because weapon systems are perceived as crucial in determining the outcome of a war, selecting weapon systems is a critical task for nations. Just as with other forms of decision analysis involving multiple criteria, selecting a weapon system poses complex, unstructured problems with a huge number of points that must be considered. Some defense analysts have committed themselves to developing efficient methodologies to solve weapon systems selection problems for the Republic of Korea''''''''s (ROK) Armed Forces. In the present study, we propose a hybrid approach for weapon systems selection that combines analytic hierarchy process (AHP) and principal component analysis (PCA) to determine the weights to assign to the factors that go into these selection decisions. These weights are inputted into a goal programming (GP) model to determine the best alternative among the weapon systems. The proposed hybrid approach that combines AHP, PCA and GP process components offsets the shortcomings posed by obscurity and arbitrariness in AHP and therefore can provide decision makers with more reasonable and realistic decision criteria than AHP alone. A case study on weapon system selection for the air force demonstrates the usefulness and effectiveness of the proposed hybrid AHP PCA GP approach. (C) 2009 Elsevier Ltd. All rights reserved.
ISSN
0360-8352
Language
English
URI
https://hdl.handle.net/10371/75003
DOI
https://doi.org/10.1016/j.cie.2009.11.013
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