Abstract
In linguistic group decision making, it is known that decision makers are individualized in understanding the meanings of words, i.e., decision makers have personalized individual semantics (PISs) in the representation of linguistic preferences. Since individuals influence each other mutually in the consensus reaching process, PISs will accordingly change. This suggests that there is an updating process of PISs for individuals. This paper proposes an endogenous and continual learning-based approach to update PISs in consensus reaching process by incorporating the endogenous consistency-driven PIS model and continual PIS learning based consensus model. Through this approach, individuals’ PISs are endogenously updated and learned while ensuring an optimal level of consistency and an increased level of collective consensus during consensus reaching process. At the end of the study, numerical examples and some simulation and comparative analyses are presented to justify the effectiveness of proposed approach.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
