Abstract
The uncertainty in the data is a hurdle in decision-making problems. Rough set theory and fuzzy set theory are built to handle the uncertainty in data. We introduce the rough bipolar fuzzy sets as a hybridization of rough sets and the bipolar fuzzy sets. After that, we discuss a group decision making problem with the data having fuzziness endowed with bipolarity and iron out this problem by applying the rough bipolar fuzzy sets. We also propose an algorithm for this problem, which yields the best decision, as well as, the worst decision between some objects.
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