The bipolar fuzzy set and bipolar soft set have inspired the development of a new frame
work called double-framed bipolar fuzzy soft sets (DFBFSSs). This structure represents
positive and negative membership information through ordered pairs, enabling a bal
anced treatment of uncertainty, imprecision, and bi-directional information in complex
decision-making scenarios. The fundamental concepts and operations of DFBFSSs are rig
orously defined and analyzed. The double-framed formulation is symmetric: exchanging
the frames preserves the structure of DFBFSSs. This symmetry enables balanced han
dling of opposing or complementary information. The key properties of the proposed
set show improved handling of uncertainty over existing fuzzy and soft set models. In
addition, a decision-making algorithm based on DFBFSSs is developed and applied to a
real-world problem to validate the framework’s feasibility. Comparative analysis confirms
the method’s robustness and advantages in uncertain, dual-information settings.
See More
See Less