The Best-Worst Method Based on Interval Neutrosophic Sets.

In real-life multi-criteria decision-making problems, decision-making data often exhibit ambiguity due to incomplete information. Additionally, qualitative judgments by decision-makers can introduce fallacies and inaccuracies. Consequently, these problems cannot be resolved using precise values alone. To address this, the present study enhances the Best-Worst Method(BWM) by incorporating interval neutrosophic sets, thereby improving its applicability to real-life multicriteria decision-making issues. In the modified BWM approach detailed in this study, decision-makers express preferences using linguistic terms, which are then converted into interval neutrosophic numbers. These numbers facilitate the comparative assessment between the best and other criteria, as well as between the other criteria and the worst criterion. All interval neutrosophic numbers are subsequently converted into real numbers using the score function s(a). Furthermore, a new nonlinear constrained optimization model concerning interval neutrosophic numbers is formulated according to the BWM framework. The resultant data, representing the weights of different criteria, do not require further transformation. A consistency ratio for BWM is also introduced to evaluate the reliability of preference comparisons. Comparative analysis of three methods using the same case study confirms the efficacy and viability of the proposed method, namely the interval neutrosophic set based BWM. [ABSTRACT FROM AUTHOR]