Study on a Model of Intelligent Group Decision-Making Based on Fuzzy Interval Similarity Degree

Abstract

By means of constructing the interval of alternative's attribute value and the similarity matrix, an intelligent group decision-making model has been established based on fuzzy interval similarity degree to solve the group multi-attribute decision-making problems with incomplete information of attribute weights and attribute effectiveness. This paper discusses the model from the following aspects: Firstly, the model uses clustering methods to get the result of ranking schemes and experts' preferences; Secondly, through the weighted Baota principles, the model aggregates the decision categories and a complex sequence is obtained; Thirdly, according to the results of decision-making, the model can rapidly analyze and process new expert's decision-making advices; Finally, an example concerning practical problems, is given to demonstrate the decision-making process. In summary, the model is certainly reasonable and practical which can achieve the goal of automatic identification, selection and updation based on the group interaction and individual preferences assembly.