Minimum-Cost Consensus Models for Group Decision Making Under Intuitionistic Fuzzy Environment
This paper mainly focuses on the consensus problems under fuzzy environment, in which experts’ original opinions take the form of intuitionistic fuzzy numbers. Based on the objective of minimizing the total consensus cost, we develop a novel intuitionistic minimum-cost consensus model (MCCM) in order to evaluate the deviation between individual opinions and group opinion. The proposed model can not only yield optimal adjusted individual opinions and consensus opinion, but also can explore index of each expert’s risk-bearing attitude. Additionally, some intuitionistic consensus models under WA operator and OWA operators are presented. With the help of multi-objective programming theory, linear-programming-based approaches are put forward to solve these consensus models. Finally, a numerical example is implemented to demonstrate the accuracy and effectiveness of the proposed models.
KeywordsGroup Decision Making Consensus Intuitionistic fuzzy number Minimum-cost consensus model Aggregation operator
The work is supported by the Humanities and Social Science Foundation of Ministry of Education in China (14YJCZH051), the National Natural Science Foundation of China (71701103, 71571104), Natural Science Foundation of Higher Education of Jiangsu Province of China under Grant (14KJB120003).
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