Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/57174
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dc.contributor.authorWen Tao Guoen_US
dc.contributor.authorVan Nam Huynhen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-05T03:35:54Z-
dc.date.available2018-09-05T03:35:54Z-
dc.date.issued2017-09-01en_US
dc.identifier.issn15729338en_US
dc.identifier.issn02545330en_US
dc.identifier.other2-s2.0-85003845781en_US
dc.identifier.other10.1007/s10479-016-2356-4en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85003845781&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/57174-
dc.description.abstract© 2016, Springer Science+Business Media New York. This paper aims at developing a proportional fuzzy linguistic distribution model for multiple attribute decision making problems, which is based on the nature of symbolic linguistic model combined with distributed assessments. Particularly, in this model the evaluation on attributes of alternatives is represented by distributions on the linguistic term set used as an instrument for assessment. In addition, this new model is also able to deal with incomplete linguistic assessments so that it allows evaluators to avoid the dilemma of having to supply complete assessments when not available. As for aggregation and ranking problems of proportional fuzzy linguistic distributions, the extension of conventional aggregation operators as well as the expected utility in this proportional fuzzy linguistic distribution model are also examined. Finally, the proposed model will be illustrated with an application in product evaluation.en_US
dc.subjectDecision Sciencesen_US
dc.titleA proportional linguistic distribution based model for multiple attribute decision making under linguistic uncertaintyen_US
dc.typeJournalen_US
article.title.sourcetitleAnnals of Operations Researchen_US
article.volume256en_US
article.stream.affiliationsJapan Advanced Institute of Science and Technologyen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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