Computational bipolar fuzzy soft matrices with applications in decision making problems

Article type: Research Article

Authors: Khan, Madad^a | Anis, Saima^a | Ahmad, Sarfraz^b | Zeeshan, Muhammad^{a; c; *}

Affiliations: [a] Department of Mathematics, COMSATS University Islamabad, Islamabad Campus, Pakistan | [b] Department of Mathematics, Abbottabad University of Science and Technology, Havelian, Pakistan | [c] Department of Mathematics, The University of Agriculture, Dera Ismail Khan, Pakistan

Correspondence: [*] Corresponding author. Muhammad Zeeshan. E-mail: [email protected].

Abstract: A fuzzy soft matrix is a type of mathematical matrix that combines the principles of fuzzy set theory and soft set theory. It is used to handle uncertainty and vagueness in decision-making problems. Fuzzy soft matrix theory cannot handle negative information. To overcome this difficulty, we define the notion of bipolar fuzzy soft (BFS) matrices and study their fundamental properties. We define products of BFS matrices and investigate some useful properties and results. We also give an application of bipolar fuzzy soft matrices to decision-making problems. We propose a decision-making algorithm based on computer programs under the environment of the bipolar fuzzy soft sets.

Keywords: Soft sets, fuzzy soft matrices, bipolar fuzzy soft matrices, BFS decision-makings

DOI: 10.3233/JIFS-221569

Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 6, pp. 10241-10253, 2023