A Feedback Mechanism Based on Granular Computing to Improve Consensus in GDM

Abstract

Group decision making is an important task in real world activities. It consists in obtaining the best solution to a particular problem according to the opinions given by a set of decision makers. In such a situation, an important issue is the level of consensus achieved among the decision makers before making a decision. For this reason, different feedback mechanisms, which help decision makers for reaching the highest degree of consensus possible, have been proposed in the literature. In this contribution, we present a new feedback mechanism based on granular computing to improve consensus in group decision making problems. Granular computing is a framework of designing, processing, and interpretation of information granules, which can be used to obtain a required flexibility to improve the level of consensus within the group of decision makers.

Description

Keywords

Group decision making, Consensus, Feedback mechanism, Granular computing

Citation

Cabrerizo, F.J. et al. (2017) A Feedback Mechanism Based on Granular Computing to Improve Consensus in GDM. In Collan, Mikael, Kacprzyk, Janusz (Eds.) Soft computing applications for group decision-making and consensus modeling. Springer, pp. 371-390

Rights

Research Institute

Institute of Artificial Intelligence (IAI)