Abstract
The Analytic Hierarchy Process (AHP) 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) 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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Marcarelli, G., Simonetti, B., Ventre, V. (2013). Analyzing AHP Matrix by Robust Regression. In: Proto, A., Squillante, M., Kacprzyk, J. (eds) Advanced Dynamic Modeling of Economic and Social Systems. Studies in Computational Intelligence, vol 448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32903-6_16
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DOI: https://doi.org/10.1007/978-3-642-32903-6_16
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