A New Multi-Attribute Decision-Making Method Based on m-Polar Fuzzy Soft Rough Sets

Muhammad Akram · Ghous Ali · N. O. Alshehri

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Fuzzy and Soft Set Theory Multi-Criteria Decision Making Rough Sets and Fuzzy Logic

Abstract

We introduce notions of soft rough m-polar fuzzy sets and m-polar fuzzy soft rough sets as novel hybrid models for soft computing, and investigate some of their fundamental properties. We discuss the relationship between m-polar fuzzy soft rough approximation operators and crisp soft rough approximation operators. We also present applications of m-polar fuzzy soft rough sets to decision-making.

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1965Fuzzy sets 1999Soft set theory—First results 2003Soft set theory 2009Soft sets combined with fuzzy sets and rough sets: a tentative approach 2010Soft sets and soft rough sets 2010Soft matrix theory and its decision making 2014m -Polar Fuzzy Sets: An Extension of Bipolar Fuzzy Sets 2015A novel algorithm for fuzzy soft set based decision making from multiobserver input parameter data set

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2020Some q-rung orthopair fuzzy hybrid aggregation operators and TOPSIS method for multi-attribute decision-making 2019Soft rough Pythagorean m-polar fuzzy sets and Pythagorean m-polar fuzzy soft rough sets with application to decision-making 2019m-Polar ( α , β ) -Fuzzy Ideals in BCK/BCI-Algebras 2019Novel m—Polar Fuzzy Linguistic ELECTRE-I Method for Group Decision-Making 2021Novel MCGDM analysis under m-polar fuzzy soft expert sets 2019MAGDM for agribusiness in the environment of various cubic m-polar fuzzy averaging aggregation operators

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