Research Of Decision-making Method Based On Fuzzy Soft Set Theory

In the real world,decision making is widely seen in every aspect of social life as a common behavior in daily life.Because the real world is complex and changeable,a lot of information in life is uncertain and fuzzy.Therefore,many decision-making problems have uncertainty and fuzziness,which affect our decision making.In order to solve these uncertain decision problems,such as probability theory,interval number theory,fuzzy set theory and rough set theory,these theories have their own shortcomings,mainly the problem of the lack of parameterized tools.In view of this shortcoming,Russian scholar Molodtsov puts forward the theory of soft set of parameters without restriction from the point of view of parameterization.Based on the soft set theory,Maji puts forward the fuzzy soft set theory which describes the object from two aspects of parameterization and degree.The rich information description makes it widely used in the fields of decision analysis,data mining and artificial intelligence,especially in its multi-attribute decision-making applications have been widely concerned and become a new popular research field.The thesis mainly study the parameters reduction problem of fuzzy soft sets and the multi-attribute decision-making method based on dynamic interval-valued fuzzy soft sets and dynamic hesitant fuzzy soft sets.The specific research contents are as follows:1.In order to solve the problem of low efficiency of parameter reduction and unreasonable parameter reduction in fuzzy soft set multi attribute decision making,a new method for parameter reduction of fuzzy soft sets based on parameter approximation is proposed.This method introduced the definition of degree of approximation to reflect the importance of the parameters in the reduction process,and used the distinguish the matrix to reduce the parameters of the fuzzy soft set.Therefore,the problem of reducing the amount of calculation was solved,the efficiency and quality of the parameter reduction were improved,and the dimension of the attribute parameter was reduced.By comparing the method of parameter reduction,it is verified that the method of parameter reduction based on parameter approximation is more reasonable and the result is more accurate.2.Aiming at the problem that the attribute weight of interval-valued fuzzy soft sets in the decision-making process is often neglected or determined by subjective experience,a method of attribute weight determination based on attribute dominance isproposed and its related properties and operations are discussed.In the process of interval-valued fuzzy soft set decision-making,the dynamic interval-valued fuzzy soft set is defined according to the characteristics of decision-making information which changes with time,and the formula of time weight for logarithmic growth based on decision time difference is established.Finally,it is verified that the dynamic interval-valued fuzzy soft set decision method based on attribute weights is more reasonable and effective by comparing and analyzing with other decision methods.3.Aiming at the shortcoming of uncertain time weight in decision making process,an incremental decreasing model is proposed to determine the time weight,and a decision method of dynamic hesitant fuzzy soft set is proposed by combining the D-S evidence theory to determine the attribute weight.Finally,by comparing with other decision-making methods,the feasibility and correctness of the dynamic hesitant fuzzy soft set decision method considering the attribute weight is verified,and the function of flexible dynamic decision is realized,and the decision result is more reasonable.