A New Clustering Algorithm With Preference Adjustment Cost to Reduce the Cooperation Complexity in Large-Scale Group Decision Making

In large-scale group decision making (LSGDM), appropriate clustering analysis is important to consensus reaching since it can reduce the interactive complexity among individuals. According to the traditional clustering method, a conflict may arise between the consensus reaching levels and total adju...

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Veröffentlicht in:	IEEE transactions on systems, man, and cybernetics. Systems Jg. 52; H. 8; S. 5271 - 5283
Hauptverfasser:	Wu, Tong, Liu, Xinwang, Qin, Jindong, Herrera, Francisco
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.08.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adjustment cost Algorithms Cluster analysis Clustering Clustering algorithms clustering analysis Complexity Complexity theory consensus reaching process Costs Decision analysis Decision making Extraterrestrial measurements large-scale group decision making (LSGDM) Linguistics Preferences Proposals
ISSN:	2168-2216, 2168-2232
Online-Zugang:	Volltext
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