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How to derive priorities in AHP: a comparative study

  • Alessio Ishizaka


  • Markus Lusti


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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. Copyright Springer-Verlag 2006

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    Article provided by Springer in its journal Central European Journal of Operations Research.

    Volume (Year): 14 (2006)
    Issue (Month): 4 (December)
    Pages: 387-400

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    Handle: RePEc:spr:cejnor:v:14:y:2006:i:4:p:387-400
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    1. Golany, B. & Kress, M., 1993. "A multicriteria evaluation of methods for obtaining weights from ratio-scale matrices," European Journal of Operational Research, Elsevier, vol. 69(2), pages 210-220, September.
    2. Brugha, Cathal M., 2000. "Relative measurement and the power function," European Journal of Operational Research, Elsevier, vol. 121(3), pages 627-640, March.
    3. Takeda, E. & Cogger, K. O. & Yu, P. L., 1987. "Estimating criterion weights using eigenvectors: A comparative study," European Journal of Operational Research, Elsevier, vol. 29(3), pages 360-369, June.
    4. Cook, Wade D. & Kress, Moshe, 1988. "Deriving weights from pairwise comparison ratio matrices: An axiomatic approach," European Journal of Operational Research, Elsevier, vol. 37(3), pages 355-362, December.
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