Adaptive consensus model with multiplicative linguistic preferences based on fuzzy information granulation
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所属单位：经济与管理学院
发表刊物：APPLIED SOFT COMPUTING
关键字：Group decision-making (GDM) Multiplicative linguistic preference relations (MLPRs) Fuzzy information granulation (fuzzy IG) Consistency measure Consensus reaching process (CRP)
摘要：An adaptive consensus model based on fuzzy information granulation (fuzzy IG) is presented for group consensus decision-making problems with multiplicative linguistic preference relations (MLPRs). Firstly, a granular representation of linguistic terms is concerned with the triangular fuzzy formation of a family of information granules over given Analytical Hierarchy Process (AHP) numerical scales. On this basis, the individual consistency and group consensus measure indices using fuzzy granulation technique are constructed, respectively. Then, the optimal cut-off points of fuzzy information granules are obtained by establishing a multi-objective optimization model together with a multi-objective particle swarm optimization (MOPSO) algorithm. A novel group consensus decision-making approach where consensus reaching process (CRP) is achieved by adaptively adjusting individual preferences through the optimization of the cut-off points is proposed. After conflict elimination, the obtained group preference gives the ranking of the alternatives. Finally, a real emergency decision-making case for liquid ammonia leak is given to illustrate the application steps of the proposed method and comparative analysis with the existing GDM methods. Comparative results demonstrate that the proposed method has some advantages in aspects of avoiding information loss or distortion and improving consensus performance. (C) 2017 Elsevier B.V. All rights reserved.
ISSN号：1568-4946
是否译文：否
发表时间：2017-11-01
合写作者：Zhang, Shitao,Liu, Xiaodi,陈晔,Ma, Zhenzhen
通讯作者：朱建军