A Granular Computing-Based Model for Group Decision-Making in Multi-Criteria and Heterogeneous Environments

dc.contributor.author Cabrerizo, Francisco
dc.contributor.author González-Quesada, Juan Carlos
dc.contributor.author Pérez, Ignacio
dc.contributor.author Herrera-Viedma, Enrique
dc.date.accessioned 2021-12-24T17:36:31Z
dc.date.available 2021-12-24T17:36:31Z
dc.date.issued 2022-01-04
dc.description.abstract Granular 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.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2022.262
dc.identifier.isbn 978-0-9981331-5-7
dc.identifier.uri http://hdl.handle.net/10125/79594
dc.language.iso eng
dc.relation.ispartof Proceedings of the 55th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Soft Computing: Theory Innovations and Problem Solving Benefits
dc.subject consensus
dc.subject consistency
dc.subject decision-making
dc.subject granular computing
dc.subject minimum adjustment
dc.title A Granular Computing-Based Model for Group Decision-Making in Multi-Criteria and Heterogeneous Environments
dc.type.dcmi text
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