Type-2 fuzzy envelope of extended hesitant fuzzy linguistic term set: Application to multi-criteria group decision making. (July 2022)

• Record Type: Journal Article
• Authors: Liu, Yaya; Rodríguez, Rosa M.; Qin, Jindong; Martínez, Luis
• Is Part Of: Computers & industrial engineering. Volume 169(2022)
• Publication Date: 2022-07
• Subjects: Extended hesitant fuzzy linguistic term set -- Rough comparative linguistic expression -- Type-2 fuzzy envelope -- Multi-criteria group decision making; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108208
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Several novel semantic representation models of EHFLTS are proposed. A new syntax is developed from a grammar that generates linguistic expression. A MCGDM model dealing with EHFLTS is developed. The proposed MCGDM model is applied to cross border e-commerce. Novel similarity measures of EHFLTS are proposed and applied in MCGDM. Abstract: Multi-criteria group decision making (MCGDM) is a common activity in human-beings' daily life. In real-world problems is common that decision makers prefer to use linguistic values instead of numerical values to express their opinions/preferences on the alternatives. Solving MCGDM problems under linguistic environment suffers difficulties such as loss of information during the computing with words (CWW) processes. Existing fuzzy encoding technology is still limited to single word, thus it is difficult to apply previous fuzzy encoding methodologies to carry out CWW processes when more complex linguistic information appears in MCGDM. To overcome these limitations, a novel MCGDM method has been proposed, in which extended hesitant fuzzy linguistic term sets (EHFLTS) is applied to decrease information loss in preference aggregation process. Novel type-1 and type-2 fuzzy envelopes of EHFLTS are proposed to decrease information loss in CWW processes. A new context-free grammar and the notion of rough comparative linguistic expression (RCLE) are introduced to supplement the computation with fuzzy envelopes of EHFLTS, and to increase the flexibility of preference elicitation. The proposed fuzzy encoding models and syntax extend the fuzzy perceptual computing technology from single words to EHFLTS and RCLE. Finally, the proposed MCGDM method which adopts fuzzy envelopes of EHFLTS is applied in a cross-border e-commerce selection situation.