Fuzzy decision making and consensus: Challenges

Abstract

Abstract. Group decision making is part of every organizational life. It is a type of participatory process in which multiple decision makers acting collectively, analyze problems, consider and evaluate several alternatives, and select from among the alternatives a solution. In such a situation, an important issue is the level of agreement or consensus achieved among the group of decision makers before obtaining the solution. In the beginning, consensus was meant as a full and unanimous agreement. Regrettably, this stringent concept of consensus in many cases is a utopia. As a result, and from a pragmatic point of view, it makes more sense to speak about a degree of consensus and, here, the theory of fuzzy sets has delivered new tools for the analysis of such imprecise phenomena like consensus. Given the significance of reaching an accepted solution by all the decision makers, consensus is a major aim of group decision making problems and, in such a way, it has obtained a great attention in the literature. However, there still exist several dares which have to be tackled by the researchers. The purpose of this paper is to bring out several issues that represent challenges that have to be faced.

Analysing discussions in social networks using group decision making methods and sentiment analysis

“…• Consensus calculation [3,23]: Calculating consensus measures can help us to know if the experts have reached an agreement or, on the contrary, they need more debate in order to reach a reasonable level of consensus. It is important, in order to improve the reliability of the decision making results, to allow experts to carry out a thorough debate before reaching a final decision.…”

Group decision-making based on heterogeneous preference relations with self-confidence

“…It will be an interesting future research to find out possible relationships among preferences, self-confidence assessments and results. Meanwhile, the consensus problem is a hot topic in GDM [2,7,10,17,32,37], and it will be interesting to investigate the consensus reaching model in GDM based on heterogeneous preference relations with self-confidence.…”

An analysis of consensus approaches based on different concepts of coincidence

“…This concept allows the definition of soft consensus criteria which are the basis of numerous consensus approaches [1,33,39,43,44,45,49,53]. In such a way, consensus measures assessed in [0,1] are introduced, where 0 means null consensus, 1 means total consensus, and values in (0,1) mean diverse partway consensus situations [4,5,13,19]. Then, a process of reaching consensus could be established as a multistage process iteratively developed and made up of several discussion and consensus rounds [12,19,20].…”