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Mathematical Support for the Geometric Mean when Deriving a Consistent Matrix from a Pairwise Ratio Matrix

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A ratio pairwise comparison matrix estimates another matrix of true ratios between objects. From the pairwise comparison matrix, various methods are used to derive a priority vector and associated consistent matrix that also estimates the matrix of true ratios. The distance from the consistent matrix and the true matrix measures the accuracy of a method. The geometric mean is shown to be the only method with error below a basic threshold while being invariant to any reordering and rescaling of columns. Besides being simple to calculate, the geometric mean has excellent performance and many desirable properties.
Wydawca
Rocznik
Strony
263--278
Opis fizyczny
Bibliogr. 12 poz., rys., tab.
Twórcy
autor
  • Beedie School of Business, Simon Fraser University, Burnaby, B.C., Canada
autor
  • Beedie School of Business, Simon Fraser University, Burnaby, B.C., Canada
  • TNO Organisation for Applied Scientific Research, The Hague, The Netherlands
Bibliografia
  • [1] Saaty TL. The Analytic Hierarchy Process, Planning, Piority Setting, Resource Allocation. New York: McGraw-Hill; 1980.
  • [2] Choo EU, Wedley WC. A common framework for deriving priority values from pairwise comparison matrices. Computers and Operations Research. 2004;31(6):893–908. doi:10.1016/S0305-0548(03)00042-X.
  • [3] Choo EU, Wedley WC. Estimating Ratio Scale Values when Units are Unspecified. Computers and Industrial Engineering Journal. 2010;59(2):200–208. doi:10.1016/j.cie.2010.04.001.
  • [4] Lin CC. A revised framework for deriving priority values from pairwise comparison matrices. European Journal of Operational Research. 2007;176(2):1145–1150. doi:10.1016/j.ejor.2005.09.022.
  • [5] Zahedi F. A simulation study of estimation methods in the analytic hierarchy process. Socio-Economic Planning Sciences. 1986;20(6):347–354. Available from: http://EconPapers.repec.org/RePEc:eee:soceps:v:20:y:1986:i:6:p:347-354.
  • [6] Bajwa G, Choo EU, Wedley WC. Effectiveness analysis of deriving priority vectors from reciprocal pairwise comparison matrices. Asia Pacific Journal of Operational Research. 2008;25(279):279–299. doi:10.1142/S0217595908001754.
  • [7] Schoner B, Wedley WC, Choo EU. A unified approach to AHP with linking pins. European Journal of Operational Research. 1993;64(3):387–392. doi:10.1016/0377-2217(93)90128-A.
  • [8] Saaty TL. Theory and Applications of the Analytic Network Process. RWS Publications, 4922 Ellsworth Avenue, Pittsburgh, PA 15213; 2005.
  • [9] Saaty TL. Relative measurement and its generalization in decision-making – Why pairwise comparisons are central in mathematics for the measurement of intangible factors: The Analytic Hierarchy/Network Process. RACSAM, Revista de la Real Academia de Ciencias Serie A: Matem´aticas. 2008;102(2):251–318. doi:10.1007/BF03191825.
  • [10] Crawford G, Williams C. A note on the analysis of subjective judgment matrices. Journal of Mathematical Psychology. 1985;29(4):387–405. doi:10.1016/0022-2496(85)90002-1.
  • [11] Fichtner J. On deriving priority vectors from matrices of pairwise comparisons. Socio-Economic Planning Sciences. 1986;20(6):341–345. Available from: http://EconPapers.repec.org/RePEc:eee:soceps:v:20:y:1986:i:6:p:341-345.
  • [12] Barzilai J. Deriving weights from pairwise comparison matrices. Journal of the Operational Research Society. 1997;48(2):1226–1233. doi:10.2307/3010752.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b8477117-f3af-4f78-a7f4-6d86125f34a8
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