Uncertainties play a dominant role during the aggregation process and hence their corresponding decisions are made fuzzier. Single-value neutrosophic numbers (SVNNs) contain the three ranges: truth, indeterminacy, and falsity membership degrees, and are very useful for describing and handling the uncertainties in the day-today life situations. In this study, some operations of SVNNs such as sum, product, and scalar multiplication are defined under Frank norm operations and, based on it, some averaging and geometric aggregation operators have been developed. We further establish some of its properties. Moreover, a decision-making method based on the proposed operators is established and illustrated with a numerical example.
Neutrosophic set, initiated by Smarandache, is a novel tool to deal with vagueness considering the truth, indeterminacy and falsity memberships satisfying the condition that their sum is less than 3. This set can be used to characterize the information more accurately than the intuitionistic fuzzy set. Under this set, the objective of this manuscript is to present some new operational laws called as logarithm operational laws with real number base k for the single-valued neutrosophic (SVN) numbers. Various desirable properties of the proposed operational laws are contemplated. Further, based on these laws, different weighted averaging and geometric aggregation operators are developed. The properties such as idempotency, monotonicity, boundedness are provided to support the proposed operators. Then, we utilized these operations and operators to present a multiattribute decision making method to solve the decision-making problems. A real numerical example is given to demonstrate the approach under SVN environment. The legitimacy of the proposed strategy is exhibited with a numerical illustration and compared the results with the several existing approaches result.
The neutrosophic set (NS) is a more general platform which generalizes the concept of crisp, fuzzy, and intuitionistic fuzzy sets to describe the membership functions in terms of truth, indeterminacy, and false degree. Under this environment, the present paper proposes an improved score function for ranking the single as well as interval-valued NSs by incorporating the idea of hesitation degree between the truth and false degrees. Shortcomings of the existing function have been highlighted in it. Further, the decision-making method has been presented based on proposed function and illustrates it with a numerical example to demonstrate its practicality and effectiveness.
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