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Building consensus in group decision making with an allocation of information granularity

Fuzzy Sets and Systems
DOI: 10.1016/j.fss.2014.03.016
  • Group Decision Making
  • Consensus
  • Consistency
  • Granularity Of Information
  • Particle Swarm Optimization


Abstract Consensus is defined as a cooperative process in which a group of decision makers develops and agrees to support a decision in the best interest of the whole. It is a questioning process, more than an affirming process, in which the group members usually modify their choices until a high level of agreement within the group is achieved. Given the importance of forming an accepted decision by the entire group, the consensus problem has attained a great attention as it is a major goal in group decision making. In this study, we propose the concept of the information granularity being regarded as an important and useful asset supporting the goal to reach consensus in group decision making. By using fuzzy preference relations to represent the opinions of the decision makers, we develop a concept of a granular fuzzy preference relation where each pairwise comparison is formed as a certain information granule (say, an interval, fuzzy set, rough set, and alike) instead of a single numeric value. As being more abstract, the granular format of the preference model offers the required flexibility to increase the level of agreement within the group using the fact that we select the most suitable numeric representative of the fuzzy preference relation.

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