Research On Multi-Granular Hesitant Fuzzy Linguistic Information Fusion And Consensus Decision Making

Hesitant fuzzy linguistic information can express the qualitative decision-making information of decision-makers flexibly and comprehensively.With the development of network technology and the promotion of social needs,decision-makers with different cultural and educational backgrounds can use different granular linguistic term sets to participate in the decision making process.This paper gives the integration and transformation method of multi-granular hesitant fuzzy linguistic term sets,a personalized dynamic feedback model based on minimum adjustment amount is established in the multi-granular fuzzy linguistic information environment.The structure of this paper is as follows.In the first chapter,we introduce the research background of multi-granular linguistic information fusion and group consensus,as well as the preliminary knowledge related to hesitant fuzzy linguistic term set and multi-granular linguistic information transformation.In the second chapter,we investigate the integration and transformation problems of multi-granular hesitant fuzzy linguistic information.Firstly,the concept of membership linguistic term set is defined,the possibility degree method for comparing membership linguistic term set is proposed and the distance measure of membership linguistic term set is defined.Then,based on the interval semantics of linguistic term sets,the method of converting multi-granular hesitant fuzzy linguistic term sets to membership linguistic term sets under the target linguistic term set is developed.Moreover,in order to interpret the results of group fusion under the original granular,we give a formula to transform the membership linguistic term set under the target granular set into that under the original granular set,the method considers the semantics of linguistic term sets,and realizes the reasonable expression of the aggregation results of multi-granular linguistic term sets under original granular.Finally,the proposed method is applied to the multi-granular group decision making problem,and illustrated by a case of medical waste treatment technology selection.In the third chapter,we study the consensus of decision-makers under the membership linguistic term set.Firstly,the consensus measurement formula of membership linguistic term set at three levels(attribute,scheme and decision matrix)is given.Secondly,considering that decision-makers tend to retain their original opinions or adjust their original opinions as little as possible in the feedback process,combining the attitude consensus threshold and personalized feedback parameters,this paper presents a personalized dynamic feedback model based on the minimum adjustment amount.Finally,the proposed method is applied to multigranular and multi-attribute group decision-making problem,and illustrated by the case in Chapter 2.