Open AccessPRIORITY VECTOR ESTIMATION: CONSISTENCY, COMPATIBILITY, PRECISION
Author(s) -
Stan Lipovetsky
Publication year - 2020
Publication title -
international journal of the analytic hierarchy process
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.213
H-Index - 3
ISSN - 1936-6744
DOI - 10.13033/ijahp.v12i3.801
Subject(s) - analytic hierarchy process , pairwise comparison , computer science , compatibility (geochemistry) , consistency (knowledge bases) , weight , mathematical optimization , multiplicative function , data mining , algorithm , mathematics , artificial intelligence , operations research , mathematical analysis , geochemistry , lie algebra , pure mathematics , geology
Various methods of priority vector estimation are known in the Analytic Hierarchy Process (AHP). They include the classical eigenproblem method given by Thomas Saaty, developments in least squares and the multiplicative approach, robust estimation based on transformation of the pairwise ratios to the shares of preferences, and other approaches. In this paper, the priority vectors are completed with validation of data consistency, comparisons of vectors’ compatibility, and estimation of precision for matrix approximation by vectors. The numerical results for different data sizes and consistency show that the considered methods reveal useful features, are simple and convenient, and capable of facilitating practical applications of the AHP in solving various multiple-criteria decision making problems.