A Consensus Support System Model for Group Decision-Making Problems With Multigranular Linguistic Preference Relations

TLDR

Group decision‑making with linguistic preference relations is studied, noting that experts may employ different multigranular linguistic term sets to express their opinions. The paper proposes a consensus support system model to assist experts throughout the consensus‑reaching process in group decision‑making problems involving multigranular linguistic preferences. The model combines a multigranular linguistic methodology that unifies diverse term sets, two consensus criteria—consensus degrees and proximity measures—to quantify agreement and opinion distance, and a guidance advice system that provides feedback to steer experts toward higher consensus. The model offers two key advantages: it handles multigranular linguistic preference relations and replaces the traditional moderator with an automated guidance advice system, thereby fully automating the group decision‑making process.

Abstract

The group decision-making framework with linguistic preference relations is studied. In this context, we assume that there exist several experts who may have different background and knowledge to solve a particular problem and, therefore, different linguistic term sets (multigranular linguistic information) could be used to express their opinions. The aim of this paper is to present a model of consensus support system to assist the experts in all phases of the consensus reaching process of group decision-making problems with multigranular linguistic preference relations. This consensus support system model is based on i) a multigranular linguistic methodology, ii) two consensus criteria, consensus degrees and proximity measures, and iii) a guidance advice system. The multigranular linguistic methodology permits the unification of the different linguistic domains to facilitate the calculus of consensus degrees and proximity measures on the basis of experts' opinions. The consensus degrees assess the agreement amongst all the experts' opinions, while the proximity measures are used to find out how far the individual opinions are from the group opinion. The guidance advice system integrated in the consensus support system model acts as a feedback mechanism, and it is based on a set of advice rules to help the experts change their opinions and to find out which direction that change should follow in order to obtain the highest degree of consensus possible. There are two main advantages provided by this model of consensus support system. Firstly, its ability to cope with group decision-making problems with multigranular linguistic preference relations, and, secondly, the figure of the moderator, traditionally presents in the consensus reaching process, is replaced by the guidance advice system, and in such a way, the whole group decision-making process is automated