A novel decision-making technique based on T-rough bipolar fuzzy sets

Abstract

In this paper, we hybridize the bipolar fuzzy set (BFS) theory with T-rough sets (T-RSs) and initiate the novel idea of T-rough BFSs (T-RBFSs). The concept presented in this article has never been discussed earlier. Moreover, we investigate the axiomatic systems of T-RBFSs in detail. Meanwhile, we address a decision-making (DM) problem having data endowed with fuzziness and bipolarity in the framework of the T-RBFSs. We also propose an algorithm for this application. This algorithm facilitates tackling the case when there is a team of decision-makers instead of a single decision-maker and when the objects of one set need to be approximated by grading the objects of some other set. Moreover, a practical application of T-RBFSs in DM problems is given, accompanied by a practical example, which provides the optimal and the worst decision between some objects. Finally, a comparative analysis of the recommended study with several prevailing approaches is given to endorse the advantages of the suggested research.

Supra finite soft-open sets and applications to operators and continuity

“…This approach is free from the inherent restrictions of the foregoing approaches since it does not require previous procedures such as membership functions and equivalence relations in the theories of fuzzy sets and rough sets, respectively. According to the published monographs, soft set theory has proven to be an invaluable tool for modeling and analyzing various real-world scenarios that appeared in different disciplines such as information theory [51], economics [15], medical science [38,46], and engineering.…”