How to derive priorities in AHP: a comparative study

Alessio Ishizaka; Markus Lusti

doi:10.1007/s10100-006-0012-9

How to derive priorities in AHP: a comparative study

Alessio Ishizaka, Markus Lusti

Research output: Contribution to journal › Article › peer-review

1017 Downloads (Pure)

Abstract

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.

Original language	English
Pages (from-to)	387-400
Journal	Central European Journal of Operations Research
Volume	14
Issue number	4
DOIs	https://doi.org/10.1007/s10100-006-0012-9
Publication status	Published - Dec 2006

Access to Document

10.1007/s10100-006-0012-9

filetodownload,70633,en.pdf
“This is a post-peer-review, pre-copyedit version of an article published in Central European Journal of Operations Research. The definitive publisher-authenticated version How to derive priorities in AHP: a comparative study Ishizaka, A. & Lusti, M. Dec 2006 In : Central European Journal of Operations Research . 14, 4, p. 387-400 is available online at: http://link.springer.com/article/10.1007%2Fs10100-006-0012-9”
Accepted author manuscript (Post-print), 170 KBLicence: CC BY-SA

http://www.port.ac.uk/departments/academic/sbs/staff/downloads/filetodownload,70633,en.pdf

Cite this

@article{9f4f5d6a36b14728a8a12c0d3ed1fef0,

title = "How to derive priorities in AHP: a comparative study",

abstract = "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.",

author = "Alessio Ishizaka and Markus Lusti",

year = "2006",

month = dec,

doi = "10.1007/s10100-006-0012-9",

language = "English",

volume = "14",

pages = "387--400",

journal = "Central European Journal of Operations Research ",

issn = "1435-246X",

publisher = "Physica-Verlag",

number = "4",

}

TY - JOUR

T1 - How to derive priorities in AHP

T2 - a comparative study

AU - Ishizaka, Alessio

AU - Lusti, Markus

PY - 2006/12

Y1 - 2006/12

N2 - 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.

AB - 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.

U2 - 10.1007/s10100-006-0012-9

DO - 10.1007/s10100-006-0012-9

M3 - Article

SN - 1435-246X

VL - 14

SP - 387

EP - 400

JO - Central European Journal of Operations Research

JF - Central European Journal of Operations Research

IS - 4

ER -

How to derive priorities in AHP: a comparative study

Abstract

Access to Document

Fingerprint

Cite this