A Novel Comparative Linguistic Distance Measure Based on Hesitant Fuzzy Linguistic Term Sets and Its Application in Group Decision-Making

Abstract

Hesitant fuzzy linguistic term set (HFLTS) Comparative linguistic expression Fuzzy group decision making (FGDM) Distance measure Aggregation approach A B S T R A C T ID:p0065The linguistic approaches are required in order to assess qualitative aspects of many real problems. In most of these problems, decision makers only adopt single and very simple terms which would not reflect exactly what the experts mean for many intricate applications. Frequently, the assessments of decision making problems involve comparative linguistic expressions. Accordingly, we propose a novel distance measure between hesitant fuzzy linguistic term sets (HFLTSs) to solve fuzzy group decision making (FGDM) problems. Firstly we define the characteristic functions to describe the HFLTSs transformed from comparative linguistic expressions. Then we construct a weighted HFLTSs graph containing all notes in the HFLTSs. Distances in the graph of individual assessments are defined by measures considering diversity and specificity of HFLTS's granularity. We put forward a new approach to achieve aggregation results for group decision making to realize the minimal distances with individual assessments. Finally, numerical examples are illustrated.

Group decision support methodology based upon the multigranular generalized orthopair 2‐tuple linguistic information model

“…A context-free grammar-based approach was adopted to elicit comparative linguistic expressions (CLEs), which have a strong ability to handle complex linguistic DMPs. [59][60][61][62][63][64] We will use CLEs to convey complex linguistic expression in real DMPs and building corresponding complex decision-making approaches. On the other hand, recently, some new linguistic computational models 22,65,66 are introduced to manage multigranular linguistic distribution assessments for their application to large-scale MAGDM problems.…”

“…However, in many real‐world linguistic group DMPs, more flexible linguistic expressions than a single linguistic label are needed due to lack of data, time pressure, and inherent vagueness exhibited by DMs. A context‐free grammar‐based approach was adopted to elicit comparative linguistic expressions (CLEs), which have a strong ability to handle complex linguistic DMPs 59–64 . We will use CLEs to convey complex linguistic expression in real DMPs and building corresponding complex decision‐making approaches.…”