Study On Methods For Intuitionistic Fuzzy Multi-attribute Group Decision-making With Incomplete Information

Multi-attribute group decision-making is an important research content in the field of decision management.It is widely used in engineering management,project evaluation,enterprise bidding and economic planning.Due to the complexity of the decision-making and the limited knowledge of experts,the decision-making information is incomplete,and the result of decision cannot be obtained efficiently and scientifically.Therefore,for the problem of intuitionistic fuzzy multi-attribute group decision-making with incomplete information,such as expert weights determination,attribute information aggregation and generalized triangular intuitionistic fuzzy number ordering,this dissertation develops the following three aspects of research:(1)In the multi-attribute group decision problem with unknown expert weight,an improved bidirectional projection method is introduced to determine the weight.Firstly,decision matrix projection is introduced from the vector projection,and the bidirectional projection relative value form is employed to weaken the influence of experts' inappropriate scoring on a certain item,which causes the weight to drop sharply.Secondly,the hesitation degree information is included in the closeness degree,and the relativity of evaluation information matrix is quantified.According to the degree of similarity,the weight of experts is distributed accordingly.Finally,the feasibility and effectiveness of the method are verified by the numerical example.(2)With regard to the multi-attribute group decision-making problem of the triangular fuzzy numbers with the attribute weights and expert weights being unknown,the confidence index is constructed based on the triangular fuzzy number entropy to quantify the certitude of decision information.The triangular fuzzy number certitude degree(TFNCD)operator is introduced,of which the invariance of displacement transformation,the idempotence and the boundedness are proved.The expert weights are determined combined with the degree of support.Finally,a new method of the attribute information aggregation is proposed,and the effectiveness of the TFNCD operator and the aggregated approach are verified by the empirical analysis.It is noticeable that the approach is built on the independence of experts,where the data features of the triangular fuzzy numbers and the completely unknown weights of attributes and experts are fully considered,resulting in the objectivity and high efficiency in the information aggregation with relatively reduced computation.Hence,it provides the new information aggregation mode and solution for multi-attribute group decision-making problem with triangular fuzzy numbers.(3)In order to sort out the generalized triangular intuitionistic fuzzy numbers objectively,the triangular intuitionistic fuzzy number is extended.Firstly,?-level sets of membership and ?-level sets of non-membership lead to the new construction of comprehensive value index,while entropy function about membership and nonmembership leads to comprehensive fuzzy index.Later,the parameter ? is introduced to consider decision makers' information preference and set up comprehensive ranking index with comprehensive value index and comprehensive fuzzy index.This method fully considers the information of membership and non-membership and is enforceable in the ranking of generalized triangular intuitionistic fuzzy numbers and linear triangular intuitionistic fuzzy numbers by numerical examples.The problem of intuitionistic fuzzy multi-attribute group decision making with incomplete information is studied in the dissertation,in which the bidirectional projection method is improved to determine the expert weight,the TFNCD operator is constructed to aggregate the attribute information and the comprehensive ranking index is constructed to sort the generalized triangular intuitionistic fuzzy number.The comparison and analysis of numerical examples demonstrate that the methods can effectively solve the problem of intuitionistic fuzzy multi-attribute group decisionmaking with incomplete information,and the information utilization is more sufficient.