Fuzzy interval linguistic sets with applications in multi-attribute group decision making

Abstract

Uncertain and hesitant information, widely existing in the real-world qualitative decision making problems, brings great challenges to decision makers. Hesitant fuzzy linguistic term sets (HFLTSs), an effective linguistic computational tool in modeling and eliciting such information, have hence aroused many scholars' interests and some extensions have been introduced recently. However, these methods are based on the discrete linguistic term framework with the limited expression domain, which actually depict qualitative information using several single values. Therefore, it is hard to ensure the integrity of the semantics representation and the accuracy of the computation results. To deal with this problem, a semantics basis framework called complete linguistic term set (CLTS) is designed, which adopts a separation structure of linguistic scale and expression domain, enriching semantics representation of decision makers. On this basis the concept of fuzzy interval linguistic sets (FILSs) is put forward that employs the interval linguistic term with probability to increase the flexibility of eliciting and representing uncertain and hesitant qualitative information. For practical applications, a fuzzy interval linguistic technique for order preference by similarity to ideal solution (FIL-TOPSIS) method is developed to deal with multi-attribute group decision making (MAGDM) problems. Through the cases of movie and enterprise resource planning (ERP) system selection, the effectiveness and validity of the proposed method are illustrated.