Soft Rough q-Rung Orthopair m-Polar Fuzzy Sets and q-Rung Orthopair m-Polar Fuzzy Soft Rough Sets and Their Applications

Abstract

The notion of a q-rung orthopair fuzzy soft rough set ( $^{q}ROFSRS$ ) appeared as an extension of q-rung orthopair fuzzy set ( $^{q}ROFS$ ) and q-rung orthopair fuzzy soft set ( $^{q}ROFSS$ ) with the aid of rough set (RS) definition. Thus, $^{q}ROFSRS$ and m-polar fuzzy set ( $_{m}PFS$ ) are convenient to deal with uncertain knowledge which helps us to solve many problems in decision making. In this paper, we define the soft rough q-rung orthopair m-polar fuzzy sets ( $^{\text {q}}RO_{\text {m}}PFS$ ) and q-rung orthopair m-polar fuzzy soft rough sets ( $^{q}RO_{\text {m}}PFSRS$ ) through crisp soft and q- rung orthopair (q-RO) m-polar fuzzy soft approximation space. The related characteristics of these models are also studied. Then, we construct two new algorithms for these models to solve MADM issues. The successful application and corresponding comparative analyses proves that our proposed models are rational and effective.

Keywords

• q-rung orthopair fuzzy soft rough set
• m-polar fuzzy set
• soft rough q-rung orthopair m-polar fuzzy sets
• q-rung orthopair m-polar fuzzy soft rough sets
• multi-attribute decision making