A hybrid approach of goal programming for weapon systems selection

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

Research output: Contribution to journalArticle

52 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)521-527
Number of pages7
JournalComputers and Industrial Engineering
Volume58
Issue number3
DOIs
Publication statusPublished - 2010 Apr 1

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Keywords

  • Analytic hierarchy process
  • Goal programming
  • Multiple criteria decision analysis
  • Principal component analysis
  • Weapon systems

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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