International Journal of Intelligent Systems · 2017 · 899 citations · 34 references
BusinessDecision SciencesMathematicsDecision TheoryMulti-criteria Decision MakingUncertainty QuantificationAggregation OperatorsFuzzy LogicFuzzy Multi-criteria Decision MakingMulti-criteria Decision AnalysisDecision Support Information SystemsFuzzy Multi-criteria Decision AnalysisFuzzy SetsIntuitionistic Fuzzy Sets
The q-rung orthopair fuzzy sets (q-ROFs) are an important way to express uncertain information, and they are superior to the intuitionistic fuzzy sets and the Pythagorean fuzzy sets. Their eminent characteristic is that the sum of the qth power of the membership degree and the qth power of the degrees of non-membership is equal to or less than 1, so the space of uncertain information they can describe is broader. Under these environments, we propose the q-rung orthopair fuzzy weighted averaging operator and the q-rung orthopair fuzzy weighted geometric operator to deal with the decision information, and their some properties are well proved. Further, based on these operators, we presented two new methods to deal with the multi-attribute decision making problems under the fuzzy environment. Finally, we used some practical examples to illustrate the validity and superiority of the proposed method by comparing with other existing methods.
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L. A. Zadeh · Information and Control · 1965 · 66.1K citations
Krassimir Atanassov · Fuzzy Sets and Systems · 1986 · 16.2K citations · Full text
Intuitionistic Fuzzy Aggregation Operators
Zeshui Xu · IEEE Transactions on Fuzzy Systems · 2007 · 2.7K citations
Humanities, Mathematics, Logic +14