Enhanced minimum cost consensus model for interval type-2 fuzzy social network group decision making focusing on individual attributes and group attitude
IF 6.7 1区 工程技术Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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引用次数: 0
Abstract
In group decision-making scenarios, consensus reaching is a crucial factor for resolving conflicts of opinion among groups, and social network analysis plays a significant role in fostering group consensus. This paper constructs a social network-driven minimum cost consensus framework for interval type-2 fuzzy group decision-making problems involving different individual attributes. Firstly, this paper proposes a theoretical social network analysis by the implementation of propagation efficiency, propagation reliability and opinion similarity to generate comprehensive trust relationships. The aim is to obtain missing trust relationships and individual centrality. Secondly, a minimum cost consensus model is constructed to give recommendation advice for identified inconsistent decision-makers according to their adjustment willingness. The novelty of the model lies in its capability to consider decision-makers’ individual attributes and group attitude or behavior. Then, this paper proposes an interval type-2 fuzzy Alternative by Alternative Comparison (ABAC) method for ranking multiple alternatives which address the rank reversal problem. Lastly, a case study on the selection of alternative charging point operators illustrates the effectiveness of the proposed method, and comparison and sensitivity analysis show the advantages of the proposed method.
期刊介绍:
Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.