The Analytic Hierarchy Process (AHP) [8] 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)[12] 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 is proposed to analyze comparison matrix.

Analyzing AHP matrices by robust partial least squares regression

MARCARELLI G;SIMONETTI B;SQUILLANTE M.;VENTRE V
2007

Abstract

The Analytic Hierarchy Process (AHP) [8] 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)[12] 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 is proposed to analyze comparison matrix.
978-84-690-4561-9
Analytic Hierarchy Process; Robust Regression; Simulation Study
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12070/8382
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