Analyzing Ahp-matrices by Robust Partial Least Squares Regression
نویسندگان
چکیده
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 proposed to analyze comparison matrix.
منابع مشابه
Analyzing AHP-matrices by regression
In the analytic hierarchy process (AHP) the decision maker makes comparisons between pairs of attributes or alternatives. In real applications the comparisons are subject to judgmental errors. Many AHP-matrices reported in the literature are found to be such that the logarithm of the comparison ratio can be suÆciently well modeled by a normal distribution with a constant variance. On the basis ...
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