Confidence Based Consensus in Environments with High Uncertainty and Incomplete Information

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 potentially huge number of different alternatives, leading the experts to present uncertainty with the preferences provided. In this context, intuitionistic fuzzy preference relations play a key role as they provide the experts with means to allocate the uncertainty inherent in their proposed opinions. However, in many occasions the experts are unable to give a preference due to different reasons, there- fore effective mechanisms to cope with missing information are more than necessary. In this contribution, we present a new group decision making (GDM) approach able to estimate the missing information and at the same time implements a mechanism to bring the experts’ opinions closer in an iterative process in which the experts’ confidence plays a key role.