Determining the (non-)membership degrees in the range (0,1) independently of the decision-makers for bipolar soft sets.

Bipolar soft sets, which are a generalization of soft sets, are a very useful mathematical model for performing complex data analysis correctly since each parameter also takes into account the NOT parameter. However, in bipolar soft sets, we can express membership degrees as 0 or 1, and we cannot process data about non-membership degrees. In all proposed mathematical models, the task of expressing a (non-)membership degree in the range (0, 1) focuses on the decision-maker. In this paper, these values in (0, 1) were tried to be determined in an objective way independent of the decision-maker. For this purpose, the concepts of (NOT) bipolar relational membership degree and (NOT) bipolar relational non-membership degree have been proposed. Moreover, using these concepts, a decision-making algorithm focusing on selecting the best object is proposed. Finally, a comparison is given for the proposed algorithm by emphasizing some important points. [ABSTRACT FROM AUTHOR]