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Ishizaka, A., & Lusti, M. (2006). How to derive priorities in AHP: a comparative study. Central European Journal of Operations Research, 14(4), 387–400. Added by: Klaus D. Goepel (06 Jun 2019 13:41:04 Asia/Singapore) Last edited by: Klaus-admin (08 Jun 2019 02:32:52 Asia/Singapore) |
| Resource type: Journal Article DOI: 10.1007/s10100-006-0012-9 BibTeX citation key: Ishizaka2006 Email resource to friend View all bibliographic details  |
Categories: AHP/ANP Keywords: Analytic Hierarchy Process (AHP), eigenvector method (EVM), geometric mean method, multi-criteria decision-making, Simulation Creators: Ishizaka, Lusti Publisher: Springer Collection: Central European Journal of Operations Research |
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| Abstract |
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A heated discussion has arisen over the “best” priorities derivation method. Using a Monte Carlo simulation this article compares and evaluates the solutions of four AHP ratio scaling methods: the right eigenvalue method, the left eigenvalue method, the geometric mean and the mean of normalized values. Matrices with different dimensions and degree of impurities are randomly constructed. We observe a high level of agreement between the different scaling techniques. The number of ranking contradictions increases with the dimension of the matrix and the inconsistencies. However these contradictions affect only close priorities. |