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A Study for Obtaining Weights in Pairwise Comparison Matrix in AHP
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 Title & Authors
A Study for Obtaining Weights in Pairwise Comparison Matrix in AHP
Jeong, Hyeong-Chul; Lee, Jong-Chan; Jhun, Myoung-Shic;
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In this study, we consider various methods to estimate the weights of a pairwise comparison matrix in the Analytic Hierarchy Process widely applied in various decision-making fields. This paper uses a data dependent simulation to evaluate the statistical accuracy, minimum violation and minimum norm of the obtaining weight methods from a reciprocal symmetric matrix. No method dominates others in all criteria. Least squares methods perform best in point of mean squared errors; however, the eigenvectors method has an advantage in the minimum norm.
AHP;Pairwise comparison matrix;Eigenvector method;Distance least squares;minimum norm;
 Cited by
계층적 의사결정론에서 일관성 지수에 대한 통계적 검정,이종찬;전명식;정형철;

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