A Best Worst Prioritization Method under a 2-tuple Linguistic Environment in Decision Making Problems

Multi-criteria group decision making (MCGDM) deals with the process of making decision among a set of
decision makers who evaluate alternatives over several criteria. MCGDM problems evolve in tandem with the
progress of society and thus, their complexity is growing. Such complexity has given rise to the large-scale
group decision making (LS-GDM) problems in which hundreds of decision makers may participate in the
decision process and there are challenges to face such as groups formation and polarization opinions. In any
MCGDM problem, the elicitation of decision makers' preferences is a key task, because the solution of the
problem is determined by this information. Pairwise comparison is a widely used technique for this task but,
a large number of comparisons might lead to erroneous solutions, since the consistency of the decision makers'
preferences could be a ected. The best-worst method (BWM) was proposed in order to reduce the number
of comparisons and consequently, the apparition of inconsistency in decision makers' opinions. However,
this proposal deals with numerical assessments, which are not enough to model uncertainty that commonly
appears in MCGDM problems. To face the latter limitation, an extension to the fuzzy environment of the
BWM was proposed, taking advantage of the use of linguistic information and of its well performance in
uncertainty modelling. Nevertheless, the latter proposal represented the results by means of triangular fuzzy
membership functions, which are hard to understand from decision makers' point of view. Therefore, in this
study, we extend the classic BWM in the 2-tuple linguistic environment to model uncertainty associated with
the pairwise judgments/comparisons via fuzzy linguistic terms and to enhance the accuracy of computation
over linguistic terms and interpretability of the results. Moreover, we apply our proposal to LS-GDM
scenarios in which polarization opinions and sub-groups identi cation that, so far, have not been addressed
from any of BWM proposals, are taken into account.