Multicriteria fuzzy decision-making method based on a novel accuracy function under interval-valued intuitionistic fuzzy environment
J Ye - Expert systems with Applications, 2009 - Elsevier
Expert systems with Applications, 2009•Elsevier
The interval-valued intuitionistic fuzzy weighted arithmetic average operator, the interval-
valued intuitionistic fuzzy weighted geometric average operator, and an accuracy function of
interval-valued intuitionistic fuzzy value are introduced in this paper. A novel accuracy
function for interval-valued intuitionistic fuzzy sets (IVIFSs) is proposed by taking into
account the unknown degree (hesitancy degree) of IVIFSs to overcome the situation of
difficult decision of existing accuracy functions to the alternatives in some cases. To identify …
valued intuitionistic fuzzy weighted geometric average operator, and an accuracy function of
interval-valued intuitionistic fuzzy value are introduced in this paper. A novel accuracy
function for interval-valued intuitionistic fuzzy sets (IVIFSs) is proposed by taking into
account the unknown degree (hesitancy degree) of IVIFSs to overcome the situation of
difficult decision of existing accuracy functions to the alternatives in some cases. To identify …
The interval-valued intuitionistic fuzzy weighted arithmetic average operator, the interval-valued intuitionistic fuzzy weighted geometric average operator, and an accuracy function of interval-valued intuitionistic fuzzy value are introduced in this paper. A novel accuracy function for interval-valued intuitionistic fuzzy sets (IVIFSs) is proposed by taking into account the unknown degree (hesitancy degree) of IVIFSs to overcome the situation of difficult decision of existing accuracy functions to the alternatives in some cases. To identify the best alternative in multicriteria decision-making problems, a multicriteria fuzzy decision-making method is established in which criterion values for alternatives are IVIFSs. We utilize the interval-valued intuitionistic fuzzy weighted aggregation operators to aggregate the interval-valued intuitionistic fuzzy information corresponding to each alternative, and then rank the alternatives and select the most desirable one(s) according to the accuracy degree of the aggregated the interval-valued intuitionistic fuzzy information corresponding to the new accuracy function. Finally, an illustrative example is given to verify the developed approach.
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