Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

There is no mathematical validity for using fuzzy number crunching in the analytic hierarchy process

There is no mathematical validity for using fuzzy number crunching in the analytic hierarchy process Abstract Fuzzy logic has difficulty producing valid answers in decision-making. Absent are theorems to prove that it works to produce results already known that are being estimated with judgments by transforming such judgments numerically. The numerical representation of judgments in the AHP is already fuzzy. Making fuzzy judgments more fuzzy does not lead to a better more valid outcome and it often leads to a worse one. The compatibility index of the AHP is used to illustrate how the answers obtained by fuzzifying AHP judgments do not produce better results than direct derivation of the principal eigenvector. Other authors who did experiments with given data in decision making quoted in the conclusions section of the paper, have observed that fuzzy sets gives the poorest answers among all methods used to derive best decisions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png "Journal of Systems Science and Systems Engineering" Springer Journals

There is no mathematical validity for using fuzzy number crunching in the analytic hierarchy process

Loading next page...
 
/lp/springer-journals/there-is-no-mathematical-validity-for-using-fuzzy-number-crunching-in-2GfpunpdTx

References (7)

Publisher
Springer Journals
Copyright
2006 Systems Engineering Society of China & Springer-Verlag
ISSN
1004-3756
eISSN
1861-9576
DOI
10.1007/s11518-006-5021-7
Publisher site
See Article on Publisher Site

Abstract

Abstract Fuzzy logic has difficulty producing valid answers in decision-making. Absent are theorems to prove that it works to produce results already known that are being estimated with judgments by transforming such judgments numerically. The numerical representation of judgments in the AHP is already fuzzy. Making fuzzy judgments more fuzzy does not lead to a better more valid outcome and it often leads to a worse one. The compatibility index of the AHP is used to illustrate how the answers obtained by fuzzifying AHP judgments do not produce better results than direct derivation of the principal eigenvector. Other authors who did experiments with given data in decision making quoted in the conclusions section of the paper, have observed that fuzzy sets gives the poorest answers among all methods used to derive best decisions.

Journal

"Journal of Systems Science and Systems Engineering"Springer Journals

Published: Dec 1, 2006

There are no references for this article.