7 research outputs found

    GDM-VieweR: A new tool in R to visualize the evolution of fuzzy consensus processes

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    With the incorporation of web 2.0 frameworks the complexity of decision making situations has exponentially increased, involving in many cases many experts, and a huge number of different alternatives. In the literature we can find a great deal of methodologies to assist multi-person decision making. However these classical approaches are not prepared to deal with such a huge complexity and there is a lack of tools that support the decision processes providing some graphical information. Therefore the main objective of this contribution is to present an open source tool developed in R to provide a quick insight of the evolution of the decision making by means of meaningful graphical representations. Thanks to the modular architecture of this solution this tool can be easily adapted to work with various Group decision making methodologies

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

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    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

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