On Dynamic Consensus Processes in Group Decision Making Problems


Consensus in group decision making requires discussion and deliberation between the group members with the aim to reach a decision that reflects the opinions of every group member in order for it to be acceptable by everyone. Traditionally, the consensus reaching problem is theoretically modelled as a multi stage negotiation process, i.e. an iterative process with a number of negotiation rounds, which ends when the consensus level achieved reaches a minimum required threshold value. In real world decision situations, both the consensus process environment and specific parameters of the theoretical model can change during the negotiation period. Consequently, there is a need for developing dynamic consensus process models to represent effectively and realistically the dynamic nature of the group decision making problem. Indeed, over the past few years, static consensus models have given way to new dynamic approaches in order to manage parameter variability or to adapt to environment changes. This paper presents a systematic literature review on the recent evolution of consensus reaching models under dynamic environments and critically analyse their advantages and limitations.


The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.


Group decision making, dynamic decision support systems, consensus process, multi period decision making, adaptive consensus models


Perez, I.J, Cabrerizo, F.J., Alonso, S., Dong, Y.C., Chiclana, F. and Herrera-Viedma, E. (2018) On Dynamic Consensus Processes in Group Decision Making Problems. Information Sciences, 459, pp. 20-35


Research Institute

Institute of Artificial Intelligence (IAI)