Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks

Abstract

Two processes are necessary to solve group decision making problems: a consensus process and a selection process. The consensus process is necessary to obtain a nal solution with a certain level of agreement between the experts while the selection process is necessary to obtain such a nal solution. Clearly, it is preferable that the set of experts reach a high degree of consensus before applying the selection process. In order to measure the degree of consensus, different approaches have been proposed. For example, we can use hard consensus measures, which vary between 0 (no consensus or partial consensus) and 1 (full consensus), or soft consensus measures, which assess the consensus degree in a more exible way. The aim of this paper is to analyze the different consensus approaches in fuzzy group decision making problems and discuss their advantages and drawbacks. Additionally, we study the future trends.