4.7 Article

Multiple criteria decision-making methods with completely unknown weights in hesitant fuzzy linguistic term setting

期刊

KNOWLEDGE-BASED SYSTEMS
卷 93, 期 -, 页码 135-144

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ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2015.11.008

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Multi-criteria decision making; Hesitant fuzzy linguistic term set; Entropy measure; Similarity measure; Distance measure

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As for multi-criteria decision making problems with hesitant fuzzy linguistic information, it is common that the criteria involved in the problems are associated with the predetermined weights, whereas the information about criteria weights is generally incomplete. This is because of the complexity and the inherent subjective nature of human thinking. In this circumstance, the weights of criteria can be derived by means of information entropy from the evaluation values of criteria for alternatives. To the best of our knowledge, up to now, there is no work having introduced the concept of entropy measure for hesitant fuzzy linguistic term sets (HFLTSs). Hence, in this paper, we are going to fill in this gap by developing information about how entropy measures of HFLTSs can be designed. (c) 2015 Elsevier B.V. All rights reserved.

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