Abstract
In this paper, we present a statistical criterion for accepting/rejecting the pairwise reciprocal comparison matrices in the Analytic Hierarchy Process. We have studied statistically the consistency in random matrices of different sizes. We are not agree with the traditional criterion of accepting matrices due to their inflexibility and because it is too restrictive when the size of the matrix increases. Our system is capable to adapt the acceptance requirements to different scopes and consistency’s necessities. The advantages of our consistency system is the introduction of statistical relativity in the acceptance criterion and the simplicity of the used index, the eigenvalue (λ max).
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Alonso, J.A., Lamata, M.T. (2005). A Statistical Criterion of Consistency in the Analytic Hierarchy Process. In: Torra, V., Narukawa, Y., Miyamoto, S. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2005. Lecture Notes in Computer Science(), vol 3558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11526018_8
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DOI: https://doi.org/10.1007/11526018_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27871-9
Online ISBN: 978-3-540-31883-5
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