Research On Some Problems Of Multiple Attribute Group Decision Making Under Uncertain Environment

Whether in campus,enterprise or company,there are decision-making problems,and in the face of increasingly complex social environment,more complex social structure and more complex alternatives,decision-making environment has become more uncertain.For describing the uncertainty of decision-makers'choice in uncertain environment,scientists have introduced many descriptive methods,among which hesitant fuzzy sets and intuitionistic fuzzy sets are widely used.In order to obtain consistent decision-making results,it is necessary to ensure consistency in decision-making process,that is,to ensure consistency in the information aggregation stage.In order to obtain more accurate and practical results of multi-attribute group decision-making,the order relations of hesitant fuzzy elements and intuitionistic fuzzy values and the consistency of algorithms in decision-making process are particularly important.Therefore,under this background,this paper studies the following contents:(1)Under intuitionistic fuzzy environment,the concept of two tuple fuzzy preference relation is proposed,and the additively consistency and multiplicatively consistency of two tuple fuzzy preference relation are defined;the definitions of two tuple multiplicative(additive)score function and two tuple multiplicative(additive)accuracy function are given,and they are applied to the ranking of intuitionistic fuzzy values.Two tuple aggregation operators are constructed for two tuple fuzzy preference relation,which are used for information integration of two tuple fuzzy preference relation.(2)The problem of multi-attribute group decision-making under intuitionistic fuzzy environment is studied.Based on additive consistent fuzzy preference relation,two tuple multiplicative consistent fuzzy preference relation and two tuple additive consistent fuzzy preference relation,three ranking methods of intuitionistic fuzzy values are constructed and three intuitionistic fuzzy multi-attribute group decision making algorithms are obtained.(3)In this paper,we study some shortcomings of the existing methods to rank hesitant fuzzy sets and some shortcomings of the existing hesitant fuzzy multi-attribute group decision-making methods,and give new ranking methods of the hesitant fuzzy sets.Ranking hesitant fuzzy sets by using distance measure and improved TOPSIS method.Finally,the proposed ranking method is applied to hesitant fuzzy multi-attribute group decision making.(4)In this paper,the problem of hesitant fuzzy multi-attribute group decision-making is studied,and two decision-making methods are given.When the weights'information of attributes is known,based on the original hesitant fuzzy decision information,the additive consistent fuzzy preference relation is constructed by relative closeness degree,and then the aggregation operator is used to aggregation the information of different experts and attributes.Finally,the new ranking method is used to rank the alternatives.When the attribute weights'information is unknown,the new method of determining the attribute weights proposed in this paper is used to extract the weights.Then,based on the original hesitant fuzzy decision information,the additive consistent fuzzy preference relationship is constructed by using relative closeness degree.Then,the aggregation operator is combined to aggregate different experts'and attributes'information.Finally,the alternatives are ranked according to the new ranking method.On the basis of theoretical research,this paper gives relevant examples for each decision-making method and demonstrates the feasibility of the proposed decision-making methods.The numerical results show that the advantages of the new methods proposed in this paper,which can ensure the consistency of the decision-making process,avoid the change or loss of the original decision-making information,and more in line with the actual situation.