Extended approach by using best–worst method on the basis of importance–necessity concept and its application

Abstract

In recent years, several concepts such as fuzzy sets, Z-numbers, and D-numbers have been proposed to handle real-world decision-making problems. Despite the desirable properties of these types of numbers, they do not consider the concept of Necessity. On the other hand, recently, the Best-Worst Method (BWM) has been introduced as a technique based on a systematic pairwise comparison of decision criteria. The advantage of this method is that it reduces the level of inconsistency or ambiguity in the results. Since ambiguity is associated with information, it is important to consider it in the decision-making process to boost the accuracy of findings. The main aim of this study is to reduce the ambiguity in attributing weights to the criteria by incorporating the BWM method and the Importance-Necessity concept (G-number), and to present a novel method, namely The GBWM method. By decreasing levels of ambiguity in the final results through the addition of the Necessity and Importance concepts, this method can be applied to an extensive range of practical and complex decision-making problems. To express the feasibility and usefulness of the proposed method in the real-world, two case studies have been investigated. Finally, the sensitivity analysis and a conceptual comparison with other methods have been conducted to confirm the strength and stability of this method.