The Analytic Hierarchy Process (AHP) [9] is a powerful process to help people to express priorities and make the best decision when both qualitative and quantitative aspects of a decision need to be considered. In this paper, in order to eliminate the influence of outliers, we use an approach based on Robust Partial Least Squares (R-PLS)[13] regression for the computation of the values for the weights of a comparison matrix. A simulation study to compare the results with other methods for computing the weights proposed to analyze comparison matrix

Analyzing AHP-matrices by Partial Least Squares Regression

VENTRE V
2008

Abstract

The Analytic Hierarchy Process (AHP) [9] is a powerful process to help people to express priorities and make the best decision when both qualitative and quantitative aspects of a decision need to be considered. In this paper, in order to eliminate the influence of outliers, we use an approach based on Robust Partial Least Squares (R-PLS)[13] regression for the computation of the values for the weights of a comparison matrix. A simulation study to compare the results with other methods for computing the weights proposed to analyze comparison matrix
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/390106
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