Abstract
This paper develops a novel group decision-making (GDM) approach for solving multiple-criteria group decision-making (MCGDM) problems with uncertainty. The hesitant fuzzy linguistic term sets (HFLTSs) are applied to elicit the decision makers’ linguistic preferences due to their distinguished efficiency and flexibility in representing uncertainty. However, the existing context-free grammar for linguistic description cannot allow generating the linguistic expressions completely free to limit the richness of HFLTSs, and the related methods for dealing with HFLTSs also have limitations in aggregating HFLTSs with different lengths and types. Therefore, this paper proposes extended context-free grammar and a novel GDM approach for HFLTSs, considering the advantages of the rough set theory and OWA operators. The rough set theory can manage the uncertainty existing in the fuzzy representation and deal with HFLTSs represented by the 2-tuple fuzzy linguistic model to get rough number sets. The OWA operator can aggregate these sets with different numbers of elements into an interval simply and objectively. Then, an extended VIKOR method based on the proposed GDM approach for HFLTSs is presented to solve the MCGDM problems. Finally, two examples are given to illustrate the applicability and validity of the developed GDM approach and the hesitant VIKOR method through sensitivity and comparison analysis with other existing approaches.
Highlights
Decision-making is a common activity for human beings to select the desirable alternatives in many different fields such as evaluation [1], selection [2], and improvement [3]
Such problems are always presented as multicriteria decision-making (MCDM) problems. e complexity and importance of the real-world decision problems make the inclusion of multiple points of view necessary in order to achieve a solution from the knowledge provided by a group of experts [4]. erefore, group decision-making (GDM) is a usual technique in MCDM practice. ese problems having complex processes where several criteria must be satisfied to find the desirable alternative by multiple experts or decision makers (DMs) are called multiple criteria group decision-making (MCGDM) problems
Many practical issues in various fields can be formulated into MCGDM problems, which refer to the rank given alternatives by a group of decision makers. e challenge of solving these problems is intensified when considering the uncertain information environment
Summary
Decision-making is a common activity for human beings to select the desirable alternatives in many different fields such as evaluation [1], selection [2], and improvement [3]. Since the introduction of the fuzzy set by Zadeh [5], the fuzzy set and its extensions have been widely used to express and model the fuzzy and vague information in the decision-making process. The biggest difficulty of establishing the membership degree in the GDM process is that experts may have a set of possible values. Aiming at such a situation, Torra [9] introduced hesitant fuzzy sets (HFSs) in terms of a function that returns a set of membership values for each element in the domain. HFSs have been widely used in solving MCDM problems due to their distinguished efficiency and flexibility in modeling uncertainty and vagueness in the decision- making process. Some measures for HFSs have been presented for decisionmaking [13,14,15]
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call