Improved MABAC Method for Multicriteria Group Decision Making With Trapezoidal Fuzzy Neutrosophic Numbers

Abstract

Many prestigious researchers have been exploring the issues of imprecision, inconsistency, and uncertain information in decision making, which are still challenges in developing a decision support system that is more feasible and efficient. This chapter proposes a new multicriteria group decision-making (MCGDM) strategy to overcome those issues. This strategy integrates the original MABAC method with trapezoidal fuzzy neutrosophic numbers (TrFNNs). First, the proposed method converts independent judgments from experts in the form of linguistic variables into TrFNNs and aggregates them using some aggregation operators. Next, it utilizes the functions of score and accuracy to rank the evaluated alternatives. By using the distance measure between the alternatives and the border approximation area, the proposed MABAC selects the best solution. Finally, the chapter illustrates an example of COVID-19 vaccine selection and a comparative analysis to show that the proposed MABAC has benefits to support indeterminate information and is more reasonable and practicable in handling MCGDM problems.