A proportional linguistic distribution based model for multiple attribute decision making under linguistic uncertainty

Wen-Tao Guo (), Huynh Van-Nam () and Songsak Sriboonchitta
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Wen-Tao Guo: Japan Advanced Institute of Science and Technology
Huynh Van-Nam: Japan Advanced Institute of Science and Technology
Songsak Sriboonchitta: Chiang Mai University

Annals of Operations Research, 2017, vol. 256, issue 2, No 8, 305-328

Abstract: Abstract 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.

Keywords: Computing with words; Decision making; Incomplete assessments; Linguistic modeling; Multiple attribute (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (3)

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DOI: 10.1007/s10479-016-2356-4

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