2010
DOI: 10.1016/j.ins.2009.11.046
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A flexible consensus scheme for multicriteria group decision making under linguistic assessments

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Cited by 213 publications
(94 citation statements)
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References 25 publications
(53 reference statements)
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“…After the negotiation and investigation of the experts, they determine the 2-tuple linguistic weight vector . As the stated earlier, the expert 3 D , named as the group leader, has rich experience, knowledge and speciality in university evaluation. Obviously, his importance degree is extremely high and may be 8 s but less than 8 s , therefore, the weight of expert 3 D can be represented using the linguistic 2-tuple .…”
Section: The Magdm Methods With 2-tuple Linguistic Assessment Informationmentioning
confidence: 93%
See 3 more Smart Citations
“…After the negotiation and investigation of the experts, they determine the 2-tuple linguistic weight vector . As the stated earlier, the expert 3 D , named as the group leader, has rich experience, knowledge and speciality in university evaluation. Obviously, his importance degree is extremely high and may be 8 s but less than 8 s , therefore, the weight of expert 3 D can be represented using the linguistic 2-tuple .…”
Section: The Magdm Methods With 2-tuple Linguistic Assessment Informationmentioning
confidence: 93%
“…Consequently, the five faculty candidates are to be evaluated using the 2-tuple linguistic information according to the linguistic term set: A A  by the latter. The worst alternative is 2 A by both methods, but the best alternative by the former is 4 A , while the best alternative by the latter is 3 A . Compared with the former, the main advantages of the latter mainly lie in the following:…”
Section: A Real Application To Evaluating University Faculty For Tenumentioning
confidence: 90%
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“…This approach is categorized as one of the MCDM methods in which value judgments of criteria are expressed through crisp values. However, in real situations when analyzing and quantifying different types of variables from different spheres, it is generally found that the information is imprecise and lacks crispness due to inaccurate estimates of values from decision maker judgments (Herrera et al 2008;Parreiras et al 2010). Thus, in real situations, where the information is imprecise, the alternatives can be better assessed by means of fuzzy sets or linguistic variables (Herrera et al 2008;Ashtiani et al 2009).…”
Section: Introductionmentioning
confidence: 99%