Multiple-Attribute Decision-Making Method Based on Correlation Coefficient of Probabilistic Dual Hesitant Fuzzy Information with Unknown Weights of Attribute
SONG Juan1,2, NI Zhiwei1,2, WU Wenying1,2, JIN Feifei3, LI Ping1,2,4
1. School of Management, Hefei University of Technology, Hefei 230009; 2. Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei University of Tech-nology, Hefei 230009; 3. School of Business, Anhui University, Hefei 230601; 4. College of Information Engineering, Fuyang Normal University, Fuyang 236041
Abstract:The probabilistic dual hesitant fuzzy set contains membership degree, non-membership degree and their corresponding probability information. It is an important tool to describe uncertain decision-making information. To solve the probabilistic dual hesitant fuzzy multiple-attribute decision-making problem with unknown attribute weight information, a multiple-attribute decision-making method is proposed based on the correlation coefficient of probabilistic dual hesitant fuzzy information. Firstly, the objective attribute weight is calculated by probabilistic dual hesitant fuzzy information entropy and combined with the subjective attribute weight given by decision-maker to obtain the comprehensive weight of attribute. Secondly, a correlation coefficient and a weighted correlation coefficient are proposed to measure the correlation level between decision-making information, and the excellent properties of the proposed correlation coefficients are analyzed. Finally, a multi-attribute decision-making method based on the correlation coefficient of probabilistic dual hesitant fuzzy information is designed and applied to the selection experiment of haze control strategies. Experimental results show that the proposed method produces good robustness and effectiveness.
宋娟, 倪志伟, 武文颖, 金飞飞, 李萍. 属性权重信息未知下基于概率对偶犹豫模糊信息相关性系数的多属性决策方法[J]. 模式识别与人工智能, 2022, 35(4): 306-322.
SONG Juan, NI Zhiwei, WU Wenying, JIN Feifei, LI Ping. Multiple-Attribute Decision-Making Method Based on Correlation Coefficient of Probabilistic Dual Hesitant Fuzzy Information with Unknown Weights of Attribute. Pattern Recognition and Artificial Intelligence, 2022, 35(4): 306-322.
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