INTERVAL TYPE-2 FUZZY RULE-BASED BWM APPROACH FOR SUSTAINABLE SUPPLIER SELECTION

Abstract

Fuzzy logic is a theory based on human-specific approximate reasoning. Therefore, fuzzy logic applications can bring simple and more effective solutions to situations that classical methods cannot overcome. The type-1 fuzzy set is a set, which has a continuous (crisp) membership degree to which a membership degree between 0 and 1 is assigned, and is characterised by membership functions. Type-2 fuzzy sets, which have the power to express uncertainty better, are expressed by membership functions, where the membership degrees of each element belonging to that set also specify a fuzzy set.Therefore, type-2 fuzzy sets allow us to include the membership functions uncertainty in fuzzy set theory. Using expert knowledge and using sensitivity of human to reflect the level of the decision maker influence is expressed as a fuzzy rule based system. Recently, it has been seen that fuzzy rules are frequently used together with multi-criteria decision making (MCDM) methods. Again, combining fuzzy rules with type-2 fuzzy numbers is also found. In this study, the Best Worst Method (BWM), one of the MCDM methods, has been integrated with fuzzy rules based interval type-2. The developed hybrid method was defined as Interval Type-2 Fuzzy Rule-Based BWM (IT2 FRB BWM). The proposed hybrid method has an important place when there are alternatives with similar ranking positions. Thus, even if there is a small difference in each alternative, it will show the difference better (more sensitively). This makes the proposed hybrid method forceful and unique.The proposed approach has been applied to a sustainable supplier selection problem comparatively with the BWM. The results show that the IT2 FRB BWM approach is more successful in ordering alternatives than the classical BWM method.