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

Decision making is a basic activity of human beings,which exists in all aspects of social life.There are many problems which exists uncertainty and ambiguity in real life,and these problems are difficult to use traditional mathematical tools to describe and solve.At present,the mathematical theories dealing with the uncertainty problem are: fuzzy set theory,rough set theory,interval number theory,probability theory and so on,however these theories have the problem of insufficient parameterization tools.Thus,the Russian mathematician Molodstov proposed a soft set theory,soft-concentrated parameters of non-binding,is a new theory of dealing with uncertainties.On the basis of the theoretical research of soft sets,many scholars have put forward some new theories.Maji proposed the concept of fuzzy soft sets which combined fuzzy sets with soft set theory.Fuzzy soft sets describe uncertainty from parameterization and degree of sophistication.This makes it possible to carry out more information description and operation than the fuzzy set,rough set and soft set theory.Fuzzy soft sets have been widely used in various fields,such as,Decision analysis,pattern recognition,machine learning and data mining and other fields.Especially in its multi-attribute decisionmaking applications have been widely concerned and become a new popular research field.This paper mainly study the parameters reduction problem of fuzzy soft sets and the multi-attribute decision-making method based on fuzzy soft sets.The specific research work is as follows:(1)In the process of parameter reduction about fuzzy soft set theory,there is a problem that the reduction efficiency is low and the result of parameter reduce is unreasonable.A new method of fuzzy soft set parameter reduction based on parameter similarity is proposed in this paper.This method is used to measure the importance of parameters in the process of parameter reduction by introducing the concept of parameter similarity.By using the discriminant matrix,the parameters of the fuzzy soft set are reduced,so as to solve the problem that the calculation of the parameters is reduced and the reduction efficiency is low.According to the similarity of the parameters,the parameters of the fuzzy soft set are reduced by using the distinguishable matrix to solve the problem of large computation and low efficiency,and to improve parameter reduction efficiency and quality,so that the results of parameter reduction is more reasonable and accurate.(2)In the process of fuzzy soft set multi-attribute decision-making,and it is difficult to determine the weight of the attribute parameters which results in low efficiency of decision-making.Therefore a new method of determining the entropy weight which is calculated by the notion of the importance degree and the deviation degree based on parameters,moreover entropy weight is used to determine the objective weight of attribute parameters.The dynamic weight determination method is proposed to determine the combined weight which combines the subjective weight and the objective weight,then combined with the traditional TOPSIS method,this paper proposes the method of fuzzy soft set multi-attribute decision-making based on TOPSIS with improved entropy weight.Finally,a practical example has been analyzed to verify the feasibility and effectiveness of the approach,which can realize the dynamic decision-making according to the demand and improve the efficiency of decision-making.