Research On Parameter Reduction And Decision-Making Algorithms Based On Interval-Valued Fuzzy Soft Set

Interval-valued fuzzy soft set is one of the extended models of soft set,and it is a mathematical tool for efficiently processing fuzzy information.The decision-making algorithms based on this model can provide decision-makers with specific analysis and effective judgment,so as to obtain the best decision-making object to meet the needs of decision-makers finally.However,the existing algorithms have their own limitations,and they cannot make effective decisions under certain special circumstances.The parameter reduction algorithms based on this model can remove redundant parameters,leaving the necessary parameters in the parameter set and maintaining the same description or decision-making ability as the original parameter set.However,the existing algorithms have a low reduction success rate,high computational complexity,and small application range.In order to solve the above problems,this paper proposes an Euclidean distance-based parameter reduction algorithm for interval-valued fuzzy soft set and a new decision-making algorithm based on the average table and the antitheses table for interval-valued fuzzy soft set.The work done in this article can be summarized into the following three aspects:(1)An Euclidean distance-based parameter reduction algorithm for interval-valued fuzzy soft setThis paper analyzes the existing methods such as normal parameter reduction algorithm and a parameter reduction algorithm for interval-valued fuzzy soft set based on pearson's product moment coefficient,and finds that they have the shortcomings of low reduction success rate,high computational complexity and small application range.In order to overcome the above shortcomings,this paper proposes a parameter reduction algorithm based on the Euclidean distance for interval-valued fuzzy soft set.The proposed algorithm is compared with the two existing algorithms,and it is verified that our algorithm not only has a higher reduction success rate,but also has lower computational complexity and a wider range of applications.(2)A decision-making algorithm based on the average table and the antitheses table for interval-valued fuzzy soft setExisting algorithms include a decision-making algorithm based on interval fuzzy choice value and score value and a decision-making method based on level soft set and opinion weighting vector for interval-valued fuzzy soft set.However,these two decision-making algorithms have their own limitations and cannot make effective decisions under certain special circumstances.Hence,this paper improves on the above problems and proposes a decision-making algorithm based on the average table and the antitheses table for this model.And compared the proposed algorithm with the above two decision-making algorithms in some special situations,and the results show that our algorithm has more powerful decision-making capabilities.(3)The application of parameter reduction algorithm and decision-making algorithm in real instanceThe parameter reduction algorithm and decision-making algorithm based on interval-valued fuzzy soft set proposed in this paper are respectively applied to real cases,which further proves the feasibility and validity of the two algorithms.