The Multi-Attributive Border Approximation Area Comparison (MABAC) for Multiple Attribute Group Decision Making Under 2-Tuple Linguistic Neutrosophic Environment

In this paper, we present the 2-tuple linguistic neutrosophic MABAC model based on the traditional MABAC (multi-attributive border approximation area comparison) model and some fundamental theories of 2-tuple linguistic neutrosophic information. Firstly, we briefly review the definition of 2-tuple linguistic neutrosophic sets (2TLNNSs) and introduce the score function, accuracy function, operation laws and some aggregation operators of 2TLNNs. Then, the calculation steps of traditional MABAC model are briefly presented. Furthermore, combine the traditional MABAC model with 2TLNNs information, the 2-tuple linguistic neutrosophic MABAC model is established for multiple attribute group decision making (MAGDM) and the computing steps are simply depicted. In our presented model; it's more accuracy and effective for computing the distance between each alternatives and the border approximation area (BAA). Finally, a numerical example for safety assessment of construction project has been given to illustrate this new model and some comparisons between 2TLNNs MABAC model and two 2TLNNs aggregation operators are also conducted to further illustrate advantages of the new method.