On the analytic hierarchy process and decision support based on fuzzy-linguistic preference structures

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

On the analytic hierarchy process and decision support based on fuzzy-linguistic preference structures. / Franco de los Rios, Camilo Andres.

In: Knowledge-Based Systems, Vol. 70, 2014, p. 203–211.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Franco de los Rios, CA 2014, 'On the analytic hierarchy process and decision support based on fuzzy-linguistic preference structures', Knowledge-Based Systems, vol. 70, pp. 203–211. https://doi.org/10.1016/j.knosys.2014.06.028

APA

Franco de los Rios, C. A. (2014). On the analytic hierarchy process and decision support based on fuzzy-linguistic preference structures. Knowledge-Based Systems, 70, 203–211. https://doi.org/10.1016/j.knosys.2014.06.028

Vancouver

Franco de los Rios CA. On the analytic hierarchy process and decision support based on fuzzy-linguistic preference structures. Knowledge-Based Systems. 2014;70:203–211. https://doi.org/10.1016/j.knosys.2014.06.028

Author

Franco de los Rios, Camilo Andres. / On the analytic hierarchy process and decision support based on fuzzy-linguistic preference structures. In: Knowledge-Based Systems. 2014 ; Vol. 70. pp. 203–211.

Bibtex

@article{589270c95911406a8b99806aee84c216,
title = "On the analytic hierarchy process and decision support based on fuzzy-linguistic preference structures",
abstract = "The Analytic Hierarchy Process (AHP) has received different fuzzy formulations, where two main lines of research can be identified in literature. The most popular one refers to the Extent Analysis Method, which has been subject of recent criticism, among other things, due to a number of missaplications that it may lead to. The other approach refers to the Logarithmic Least Squares Method (LLSM), which offers a constrained optimization approach for estimating fuzzy weights, but fails to generalize the original AHP proposal. The fact remains that the AHP uses linguistic evaluations as input data, where experts value pairs of alternatives/criteria with words, making it essentially fuzzy under the view that words can be represented by fuzzy sets for their respective computation. Hence, reasoning with fuzzy logic is justified by the analytical framework that it offers to design the meaning of words through membership functions and not assume a direct mapping between words and crisp numbers. In this paper we propose the fuzzy representation of linguistic preferences for the AHP, and examine its generalization by means of the fuzzy-linguistic AHP algorithm.",
author = "{Franco de los Rios}, {Camilo Andres}",
year = "2014",
doi = "10.1016/j.knosys.2014.06.028",
language = "English",
volume = "70",
pages = "203–211",
journal = "Knowledge-Based Systems",
issn = "0950-7051",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - On the analytic hierarchy process and decision support based on fuzzy-linguistic preference structures

AU - Franco de los Rios, Camilo Andres

PY - 2014

Y1 - 2014

N2 - The Analytic Hierarchy Process (AHP) has received different fuzzy formulations, where two main lines of research can be identified in literature. The most popular one refers to the Extent Analysis Method, which has been subject of recent criticism, among other things, due to a number of missaplications that it may lead to. The other approach refers to the Logarithmic Least Squares Method (LLSM), which offers a constrained optimization approach for estimating fuzzy weights, but fails to generalize the original AHP proposal. The fact remains that the AHP uses linguistic evaluations as input data, where experts value pairs of alternatives/criteria with words, making it essentially fuzzy under the view that words can be represented by fuzzy sets for their respective computation. Hence, reasoning with fuzzy logic is justified by the analytical framework that it offers to design the meaning of words through membership functions and not assume a direct mapping between words and crisp numbers. In this paper we propose the fuzzy representation of linguistic preferences for the AHP, and examine its generalization by means of the fuzzy-linguistic AHP algorithm.

AB - The Analytic Hierarchy Process (AHP) has received different fuzzy formulations, where two main lines of research can be identified in literature. The most popular one refers to the Extent Analysis Method, which has been subject of recent criticism, among other things, due to a number of missaplications that it may lead to. The other approach refers to the Logarithmic Least Squares Method (LLSM), which offers a constrained optimization approach for estimating fuzzy weights, but fails to generalize the original AHP proposal. The fact remains that the AHP uses linguistic evaluations as input data, where experts value pairs of alternatives/criteria with words, making it essentially fuzzy under the view that words can be represented by fuzzy sets for their respective computation. Hence, reasoning with fuzzy logic is justified by the analytical framework that it offers to design the meaning of words through membership functions and not assume a direct mapping between words and crisp numbers. In this paper we propose the fuzzy representation of linguistic preferences for the AHP, and examine its generalization by means of the fuzzy-linguistic AHP algorithm.

U2 - 10.1016/j.knosys.2014.06.028

DO - 10.1016/j.knosys.2014.06.028

M3 - Journal article

VL - 70

SP - 203

EP - 211

JO - Knowledge-Based Systems

JF - Knowledge-Based Systems

SN - 0950-7051

ER -

ID: 120178983