Research On Several Multiple Attribute Group Decision Making Methods Under The Fuzzy Environment And Their Applications

As an important branch of modern decision science,the theories and methods of multiple attribute decision-making have wide applications in various areas such as economics,management,military,society and so on.With the development of society,economy and information technology,people are confronted with the complexity of decision-making problems and the limitations of their knowledge,so sometimes they can not make the correct judgment in the decision making process.In order to obtain more reasonable and comprehensive decision-making results,a group of decision makers are organized to participate in the decision-making,so as to pool wisdom and reduce prejudice,and improve the level and quality of decision-making.Meanwhile,since it is difficult for decision makers to give accurate evaluation values,Zadeh firstly proposed the concept of fuzzy set,which can better describe the fuzziness of objective things and human thinking.Considering the limitations of personal experience and knowledge structure and the advantages of group decision making and fuzzy evaluation information,this thesis mainly focuses on the multi-attribute(group)decision making methods under intuitionistic fuzzy,hesitant fuzzy and dual hesitant fuzzy environments.The main work and results are as follows:(1)Propose an intuitionistic fuzzy multi-attribute group decision making method based on weighted Muirhead mean operators.Combining Einstein operation with Muirhead mean operator,new intuitionistic fuzzy weighted Muirhead mean operators are constructed.When fusing intuitionistic fuzzy information,the new operators can not only consider the weight of information,but also fuse the interaction relation of information.At the same time,the basic properties of these new operators are analyzed.Moreover,a multi-attribute group decision making method based on weighted Muirhead mean operators is proposed to solve the group decision making model under the intuitionistic fuzzy environment,when the weight information is unknown and decision makers have different opinion on weights of evaluation attributes.Finally,an investment problem has been chosen to illustrate the effectiveness and practicability of the proposed method by comparison analysis.(2)Present a multi-attribute group decision making method for incomplete intu-itionistic fuzzy preference relations based on additive consistency.Due to complex circumstance,decision makers may have difficulty in offering complete intuitionistic fuzzy preference relations in the decision making process,so that it will lead to loss of important information.Applying the additive consistency to estimate missing preference values,some obtained values may conflict with the defined domain.To address this issue,this thesis discusses the group decision making problem when the intuitionistic fuzzy preference relations are incomplete and the decision-makers’ weights are completely unknown.Firstly,we give a definition of additive consistency for intuitionistic fuzzy preference relations.Secondly,two different conditions are provided in theorems,under which the missing preference values can be estimated such that they are expressible and consistent.Thirdly,for the incomplete intuitionistic fuzzy preference relation which does not satisfy the conditions given in two theorems,a new algorithm is put forward to revise the inconsistent preference values.Furthermore,based on the mean consensus index,the weights of decision makers can be determined in the process of group decision making.An illustrative example about evaluating facade clothing systems for the clothing of a building is chosen to demonstrate the effectiveness of the proposed method.(3)Put forward a hesitant fuzzy multi-attribute group decision making method based on the weighted power aggregation operators in social network.From the viewpoint of social network analysis,decision makers are interconnected in the process of multi-attribute group decision making.In addition,with the increasing number of attribute and alternative and decision maker,the dimension of obtained element by original power operators will be greater,which will lead to the problem of“intermediate expression swell”.In order to simplify the involved calculation,this thesis combines the order operation laws with the power operator to define two novel hesitant fuzzy power aggregation operators,and discusses the properties of new operators.Meanwhile,we utilize the strength of social ties and social influence to develop an algorithm for extending the hesitant fuzzy sets objectively when two given sets have different number of values.On the other hand,the Page Rank algorithm and the deviation method are used to determine the weights of decision makers.The feasibility of the proposed hesitant fuzzy multi-attribute group decision making method based on social networkis illustrated by applications to the actual decision making problem and the comparison analysis with the existing methods.(4)Propose a dual hesitant fuzzy TOPSIS multi-attribute decision making method based on new information measures.Following the existing measure methods,the elements in dual hesitant fuzzy sets should be of equal length and thus some values must be added into the shorter elements according to the risk preference of decision makers.The extension of values will increase the subjectivity of decision-making to some extent,and different extension methods may produce different results.In order to address this issue,several new types of distance and similarity measures without adding values are proposed.According to the proposed distance and similarity measures,two entropy measures are presented from the viewpoints of complementary set and the fuzziest set,respectively.Furthermore,a new TOPSIS method based on the proposed distance and entropy measures are given for dealing with dual hesitant fuzzy multi-attribute decision-making problems.Two concrete decision-making examples are analyzed to show the validity and rationality of the proposed method.