Some Generalized Single Valued Neutrosophic Linguistic Operators and Their Application to Multiple Attribute Group Decision Making

This paper proposes a group decision making method based on entropy of neutrosophic linguistic sets and generalized single valued neutrosophic linguistic operators. This method is applied to solve the multiple attribute group decision making problems under single valued neutrosophic liguistic environment, in which the attribute weights are completely unknown. First, the attribute weights are obtained by using the entropy of neutrosophic linguistic sets. Then three generalized single valued neutrosophic linguistic operators are introduced, including the generalized single valued neutrosophic linguistic weighted averaging(GSVNLWA) operator, the generalized single valued neutrosophic linguistic ordered weighted averaging(GSVNLOWA) operator and the generalized single valued neutrosophic linguistic hybrid averaging(GSVNLHA) operator, and the GSVNLWA and GSVNLHA operators are used to aggregate information. Furthermore, similarity measure based on single valued neutrosophic linguistic numbers is defined and used to sort the alternatives and obtain the best alternative. Finally,an illustrative example is given to demonstrate the feasibility and effectiveness of the developed method.

Entropy and Similarity Measure for T2SVNSs and Its Application

The objective of this paper is to present a new approach for solving the multicriteria group decision-making(MCGDM)problems in type-2 single valued neutrosophic set(T2SVNS)environment.Firstly,we give the concepts SVNS,T2SVNS and tangent similarity measure with T2SVN information.Secondly,we define a new entropy function for determining unknown attribute weights.In addition,a MCGDM method is developed based on entropy and tangent similarity measure of T2SVNSs.Finally,an illustrative example and comparative analysis are given to confirm the rationality and feasibility of the proposed method.