Attitude-Driven Web Consensus Support System for Large-Scale GDM Problems Based on Fuzzy Linguistic Approach

In real-life Group Decision Making problems defined under uncertainty, it is usually necessary to carry out a consensus reaching process to achieve a solution that is accepted by all experts in the group. Additionally, when a high number of experts take part in such processes, it may sometimes occur that some subgroups of them with similar interests try to bias the collective opinion, which makes it more difficult to reach a collective agreement. The consensus reaching process could be optimized if the group's attitude towards consensus were integrated in it, and the complexity of dealing with large groups of experts could be reduced with the adequate automation of such a process. This paper presents a Web-based Consensus Support System for large-scale group decision making problems defined under uncertainty, that integrates the group's attitude towards consensus and allows experts to provide their preferences by means of linguistic information. The underlying consensus model of the proposed system carries out processes of Computing with Words to deal with linguistic preferences effectively.