Research On Group Decision-making Method Based On Different Intuitionistic Fuzzy Preference Relations

Due to both the complexity of practical decision-making problems and the limitations of decision-makers' working experience as well as knowledge,it is difficult for decision-makers to describe decision-making problems with accurate numerical values,which leads to the emergence of various fuzzy group decision-making(GDM)methods.Since the intuitionistic fuzzy preference relations(IFPRs),intuitionistic multiplicative fuzzy preference relations(IMFPRs)and interval intuitionistic fuzzy preference relations(IVIFPRs)can more comprehensively express the pairwise comparison between alternatives from the following three dimensions: affirmative,negative and hesitant,the GDM method based on these three preference relations have received extensive attention from researchers in recent years.However,through theoretical analysis,it is found that these existing methods have some defects in the consistency definition of preference relations,the determination of experts' weights,consensus improvement and the determination of priority weights of alternatives,which can't ensure the accuracy of decision-making results.Therefore,to make up for these defects of existing methods,the dissertation studies GDM with IFPRs,IMPRs and IMFPRs,and the main research results are listed as follows:For the research of GDM based on multiplicative consistent IFPRs,firstly,some different risk preference characteristics of experts are taken into account,and a generalized multiplicative consistency definition of IFPRs is provided.After doing so,two mathematical programming models are constructed to estimate the default value of incomplete IFPRs and improve the consistency level of IFPRs,respectively.Secondly,a comprehensive method for determining experts' weights is proposed,and then a targeted consensus improvement algorithm is developed.Meanwhile,in response to the proposed multiplicative consistency definition,a novel method for determining the optimal priority weights of alternatives is redefined.Finally,a novel GDM with generalized multiplicative consistent IFPRs is developed.For the research of GDM based on additive consistent IVIFPRs,firstly,weakly additive and strongly additive consistency definitions of IVIFPRs are proposed,respectively,and a new interactive iterative consistency improvement algorithm is designed based on the strongly consistency definition.Secondly,a bi-objective optimization model for determining experts' weights is constructed,and a new interactive iterative consensus improvement algorithm is presented.Finally,based on the weakly additive consistency definition,a novel method for determining the interval fuzzy optimal priority weights of alternatives is given.Finally,a novel GDM with acceptably additive consistent IVIFPRs is proposed.For the research of GDM based on IMFPRs,firstly,the concept of hesitation degree of IMFPRs is defined and introduced into the consistency and consensus improvement process.Furthermore,the definition of the consistency index of IMFPRs is provided,and a consistency improvement mathematical programming model is constructed.Secondly,a consensus improved mathematical programming model is presented,and a consensus improved iterative algorithm with feedback mechanism guidance and minimum adjustment characteristics is developed.After doing so,a distance-based aggregation method is used to obtain the group IMPRs involving the characteristics of expert preference.Finally,a novel GDM method with IMPRs based on minimum adjustment consensus improvement is developed.For the research of GDM with incomplete IMFPRs,firstly,a consistency definition of IMFPRs is proposed,which can quantify the consistency degree of IMFPRs,and a mathematical programming model is constructed to improve the consistency of complete IMFPRs,and then it is extended to simultaneously estimate the default value of incomplete IMFPRs and improve the consistency level of corresponding complete IMFPRs.Secondly,a mathematical programming model for determining experts' weights is constructed that considers subjective and objective factors affecting the experts' weights.Meanwhile,a consensus-improved mathematical programming model is provided,and a method for determining the priority weights of alternatives is proposed,in which the characteristics of experts' risk preferences is taken into account.Finally,a novel GDM method with incomplete(complete)IMPRs is developed.