Multiple Attribute Group Decision Making Based on 2-Tuple Linguistic Neutrosophic Dombi Power Heronian Mean Operators

As an expansion of 2-tuple linguistic intuitionistic fuzzy set, the newly developed 2-tuple linguistic neutrosophic set (2-TLNS) is more satisfactory to define decision maker’s assessment information in decision-making problems. 2-TLN aggregation operators are of great significance in multiple attribute group decision making (MAGDM) problems with a 2-tuple linguistic environment. Therefore, in this paper, our main contribution is to develop novel 2-TLN power Heronian aggregation (2-TLNPHM) operators. First, we develop new operational laws established on Dombi T-norm (DTN) and Dombi T-conorm (DTCN). Second, Taking full advantages of the power average (PA) operator and Heronian mean (HM) operator, we develop some new novel power Heronian mean operator and discuss its related properties and special cases. The main advantages of developed aggregation operators are that they not only remove the effect of awkward data which may be too high or too low but also have a good capacity to model the extensive correlation between attributes, making them more worthy for successfully solving more and more complicated MAGDM problems. Thus, we develop a new algorithm to handle MAGDM based on developed aggregation operators. Finally, we apply the proposed method and algorithm to risk assessment for the construction of engineering projects to show the efficiency of the developed method and algorithm. The dominant novelties of this contribution are triplex. First, new operational laws are proposed for 2-TLNNs. Second, novel 2-TLNPHM operators are developed. Third, a new approach for 2-tuple linguistic neutrosophic MAGDM is developed.