Research On Vague Multi-attribute Group Decision-making Method Based On Evidence Theory And Its Applicatio

In order to solve the problem of difficult decision-making in complex environment,this paper studies the Vague multi-attribute group decision-making model with the advantage of Vague sets to describe uncertain information.In the current researches of Vague multi-attribute group decision making,weight solving and information aggregation are the focus of scholars.In the studies of weight solving,existing studies focus on expert weight or attribute weight,and few studies consider the weight of Vague evaluation value.However,in the process of information aggregation,Vague evaluation value is taken as the unit,so it is necessary to consider the weight of Vague evaluation value.Through the weight of Vague evaluation value,we can see the importance of each Vague evaluation value in the process of information aggregation and its influence on the final results.In the studies of information aggregation,the current information aggregation algorithms do not consider the reasonable redistribution of the unknown degree of Vague sets,so the results cannot fully represent the original evaluation information.Aiming at the problems of weight solving and information aggregation in Vague multi-attribute group decision-making model,based on solving the weight of Vague evaluation value,this paper fuses Vague evaluation information through evidence theory,and then obtains a Vague multi-attribute group decision-making information aggregation algorithm based on evidence theory.Firstly,this paper uses the idea of solving the weight of evidence in the improved evidence theory to solve the weight of Vague evaluation value based on similarity.Secondly,this paper analyzes the mathematical relationship between Vague sets and evidence theory,and obtains the final Vague evaluation value of each alternative by fusing Vague evaluation information through evidence theory,including expert set evidence information aggregation and attribute set evidence information aggregation.In expert set evidence information aggregation,the weight of each Vague evaluation value is calculated and weighted,and then the evidence theory is used to fuse the weighted average Vague evaluation to obtain the Comprehensive Vague evaluation value.In attribute set evidence information aggregation,the weight of each comprehensive Vague evaluation value is calculated and weighted,and then the evidence theory is used to fuse the weighted average comprehensive Vague evaluation value to obtain the final Vague evaluation value.Finally,the score function is used to obtain the score and ranking of each alternative.After sorting the alternatives,the optimal alternative is selected.After obtaining the information aggregation algorithm,this paper takes the joint construction of industrial Internet platform as an example.Based on the preliminary joint construction alternative,the optimal joint alternative is obtained by using the method of this paper based on the expert scoring results.In order to verify the rationality of this method,satisfactory results are obtained by comparative study.