Triangular Intuitionistic Fuzzy Multiple Atribute Group Decision Making Method And Its Application

When faced with complex decision-making problems that need to be evaluated,due to the limitations of a single decision maker's own experience and knowledge base,it is generally difficult to give a relatively comprehensive evaluation,and triangular intuitionistic fuzzy sets(TIFs)further extend the concept of intuitionistic fuzzy sets(IFS),Can more accurately describe the evaluation information of the decision.In addition,through decision-makers' evaluation information on the attributes of alternatives,to select appropriate social media software to obtain news information,which has important practical significance for today's Internet users.Therefore,this paper summarizes the social media software evaluation into a typical TIF multiattribute group decision-making(MAGD)problem.TIFs have been widely used in practical decision-making problems in real life,and related TIF MAGD methods are also endless.However,the current research on triangular IF MAGD methods has the following three shortcomings: one is that there is little research on the similarity measurement of TIFs;second,in many studies,the weights of decision makers and attribute weights are set in advance There is a certain degree of subjective arbitrariness,which will affect the authenticity of the final decision result;third,the research on the ranking method of TIFs is not perfect.In order to make up for the above three shortcomings of the existing TIF MAGD methods,this paper introduces a new TIF number similarity measure MAGD method and applies it to social media software evaluation cases in.The main content of this article is divided into the following five aspects:1.Propose a new method for ranking IFS based on attitude risk.According to the definition,algorithm and possibility theory of TIFs,the possible mean and possible standard deviation of fuzzy numbers are defined,and the possible advantages of fuzzy numbers are further defined.The TIFs are combined with the risk preference attitude of decision makers.Sort.2.Define the weighted TIFs Tversky similarity measure.Based on the characteristics of the Tversky parameterized model and TIFs,the TIF number Tversky similarity measure and the weighted TIF number Tversky similarity measure are defined,and by adjusting the Tversky parameters,the similarity between the triangular fuzzy numbers is determined.3.A new method for determining the weight of decision makers based on social network relationships is proposed.Considering that decision makers have corresponding links in the process of group decision-making,first of all,this paper uses the TIF number Tversky similarity measure to measure the similarity between decision makers,and then constructs a similarity matrix between decision makers,and then sets Similarity threshold,construct the social network relationship between decision makers,and finally determine the weight of the decision maker through the social network relationship.4.A new method for determining attribute weights is proposed.Based on the principle of maximizing the similarity between the individual attribute evaluation value and the group attribute evaluation value of decision makers and the principle of minimizing the support of individual attribute evaluation values,a bi-objective programming model is constructed to objectively find the attribute weights of each decision maker and compare each decision The weights of the attribute weights are aggregated together to find the group attribute weights,which effectively avoids the influence of subjective factors.5.A new method of TIF multi-attribute group decision-making is proposed.Based on the above TIF number ranking method based on risk attitude,decision-maker weights,and attribute weights,this paper proposes a new TIF MAGD method,which is applied to social media software evaluation.