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Fuzzy Judgments and Fuzzy Sets

Fuzzy Judgments and Fuzzy Sets

Thomas L. Saaty, Liem T. Tran
Copyright: © 2010 |Volume: 1 |Issue: 1 |Pages: 18
ISSN: 1947-8569|EISSN: 1947-8577|ISSN: 1947-8569|EISBN13: 9781616929992|EISSN: 1947-8577|DOI: 10.4018/jsds.2010103002
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MLA

Saaty, Thomas L., and Liem T. Tran. "Fuzzy Judgments and Fuzzy Sets." IJSDS vol.1, no.1 2010: pp.23-40. http://doi.org/10.4018/jsds.2010103002

APA

Saaty, T. L. & Tran, L. T. (2010). Fuzzy Judgments and Fuzzy Sets. International Journal of Strategic Decision Sciences (IJSDS), 1(1), 23-40. http://doi.org/10.4018/jsds.2010103002

Chicago

Saaty, Thomas L., and Liem T. Tran. "Fuzzy Judgments and Fuzzy Sets," International Journal of Strategic Decision Sciences (IJSDS) 1, no.1: 23-40. http://doi.org/10.4018/jsds.2010103002

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Abstract

Using fuzzy set theory has become attractive to many people. However, the many references cited here and in other works, little thought is given to why numbers should be made fuzzy before plunging into the necessary simulations to crank out numbers without giving reason or proof that it works to one’s advantage. In fact it does not often do that, certainly not in decision making. Regrettably, many published papers that use fuzzy set theory presumably to get better answers were not judged thoroughly by reviewers knowledgeable in both fuzzy theory and decision making. Buede and Maxwell (1995), who had done experiments on different ways of making decisions, found that fuzzy does the poorest job of obtaining the right decision as compared with other ways. “These experiments demonstrated that the MAVT (Multiattribute Value Theory) and AHP (Analytic Hierarchy Process) techniques, when provided with the same decision outcome data, very often identify the same alternatives as ‘best’. The other techniques are noticeably less consistent with the Fuzzy algorithm being the least consistent.”

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