Abstract
In group decision making problems, a natural question in the consensus process is how to measure the closeness among experts’ opinions in order to obtain the consensus level. To do so, different approaches have been proposed. For instance, several authors have introduced hard consensus measures varying between 0 (no consensus or partial consensus) and 1 (full consensus or complete agreement). However, consensus as a full and unanimous agreement is far from being achieved in real situations. So, in practice, a more realistic approach is to use softer consensus measures, which assess the consensus degree in a more flexible way. The aim of this paper is to identify the different existing approaches to compute soft consensus measures in fuzzy group decision making problems. Additionally, we analyze their advantages and drawbacks and study the future trends.Keywordsgroup decision makingconsensus processsoft consensus measures
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