期刊
INFORMATION SCIENCES
卷 547, 期 -, 页码 689-709出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2020.08.042
关键词
Large-scale group decision making; Social circle; Three-way decision; Ego network; Evidence theory; Preference
资金
- National Key Research and Development Program of China [2017YFA0700300]
- National Natural Science Foundation of China [61733009, 61973332]
- Natural Sciences Foundation of Guangdong Province [2018B030311054]
This paper proposes an evidential three-way theoretic model for large-scale group decision analysis, introducing the concept of ego networks and utilizing social influence network (SIN) technique and fuzzy preference relation (FPR) model for preference evolution. By comparing with related methods, the proposed method is believed to reasonably solve real-world large-scale group decision-making problems with good practicality and effectiveness.
Social relationships are critical to the group decision-making (GDM) process, especially for large-scale scenarios. Conventional GDM models have several drawbacks when applied to large-scale GDM problems. In this paper, we propose an evidential three-way theoretic model for large-scale group decision analysis based on the introduction of ego networks. A similarity matrix of all individuals is obtained after ego network generation via social network feature extraction. Rough and smooth detection are then conducted in the framework of three-way decisions. Specifically, the degree of organizational influence is analyzed based on the generated basic probability assignments (BPAs), and the individuals are divided into several organizations. After an opinion collection process, preference evolution is implemented via a social influence network (SIN) technique and a fuzzy preference relation (FPR) model. Then, the global final scores of all the alternatives are obtained using an aggregation process. Finally, we conduct a simulation experiment to illustrate the entire procedure. Based on a comparison of related methods, we believe that the proposed method can reasonably solve real-world large-scale group decision-making (LSGDM) problems and has good practicability and effectiveness. (C) 2020 Elsevier Inc. All rights reserved.
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