FUZZY MULTI-ATTRIBUTE DECISION MAKING METHOD BASED ON NEW SIMILARITY MEASUREMENT UNDER SINGLE-VALUED NEUTROSOPHIC SETS

Single-valued neutrosophic number (SVNN) is widely used in multiple attribute decision making especially when the judgment information is not accurate. The similarity measurement of single-valued neutrosophic sets (SVNSs) is an important step involved in SVNN. In this paper, the grey system theory is used first to determine the objective weight, and then the objective weight is combined with the subjective weight to form the combined weight. Then the information of alternatives with different attributes is described in the form of SVNN. In the following process of decision-making, a new similarity measurement between SVNSs based on geometric mean minimization operator is proposed to compare each alternative with the ideal optimal solution and the similarity between them is calculated which will result in the best alternative. Finally, an example is applied to illustrate the effectiveness and practicability of the proposed method