Cabrerizo, FranciscoGonzález-Quesada, Juan CarlosPérez, IgnacioHerrera-Viedma, Enrique2021-12-242021-12-242022-01-04978-0-9981331-5-7http://hdl.handle.net/10125/79594Granular computing is a growing computing paradigm of information processing that covers any techniques, methodologies, and theories employing information granules in complex problem solving. Within the recent past, it has been applied to solve group decision-making processes and different granular computing-based models have been constructed, which focus on some particular aspects of these decision-making processes. This study presents a new granular computing-based model for group decision-making processes defined in multi-criteria and heterogeneous environments that is able to improve with minimum adjustment both the consistency associated with individual decision-makers and the consensus related to the group. Unlike the existing granular computing-based approaches, this new one is able to take into account a higher number of features when dealing with this kind of decision-making processes.10 pagesengAttribution-NonCommercial-NoDerivatives 4.0 InternationalSoft Computing: Theory Innovations and Problem Solving Benefitsconsensusconsistencydecision-makinggranular computingminimum adjustmenttext10.24251/HICSS.2022.262