Research article

Extending neutrosophic set theory: Cubic bipolar neutrosophic soft sets for decision making

  • Received: 12 August 2024 Revised: 19 September 2024 Accepted: 21 September 2024 Published: 26 September 2024
  • MSC : 03B52, 03E72

  • This research introduced cubic bipolar neutrosophic sets (CBNSs), a novel framework that significantly enhanced the capabilities of bipolar neutrosophic sets (BNSs) in handling uncertainty and vagueness within data analysis. By integrating bipolarity and cubic sets, CBNSs provide a more comprehensive and accurate representation of information. We have defined key operations for CBNSs and thoroughly investigated their structural properties. Additionally, we have introduced cubic bipolar neutrosophic soft sets (CBNSSs) as a flexible parameterization tool for CBNSs. To validate the practical utility of CBNSs, we conducted a case study in decision-making. Our algorithmic approach effectively addressed the challenges posed by uncertainty and vagueness in the decision-making process. The results of our research unequivocally demonstrated the superiority of CBNSs over existing methods in terms of accuracy, flexibility, and applicability. By offering a more nuanced representation of information, CBNSs provide a valuable tool for researchers and practitioners tackling complex decision problems.

    Citation: Khulud Fahad Bin Muhaya, Kholood Mohammad Alsager. Extending neutrosophic set theory: Cubic bipolar neutrosophic soft sets for decision making[J]. AIMS Mathematics, 2024, 9(10): 27739-27769. doi: 10.3934/math.20241347

    Related Papers:

  • This research introduced cubic bipolar neutrosophic sets (CBNSs), a novel framework that significantly enhanced the capabilities of bipolar neutrosophic sets (BNSs) in handling uncertainty and vagueness within data analysis. By integrating bipolarity and cubic sets, CBNSs provide a more comprehensive and accurate representation of information. We have defined key operations for CBNSs and thoroughly investigated their structural properties. Additionally, we have introduced cubic bipolar neutrosophic soft sets (CBNSSs) as a flexible parameterization tool for CBNSs. To validate the practical utility of CBNSs, we conducted a case study in decision-making. Our algorithmic approach effectively addressed the challenges posed by uncertainty and vagueness in the decision-making process. The results of our research unequivocally demonstrated the superiority of CBNSs over existing methods in terms of accuracy, flexibility, and applicability. By offering a more nuanced representation of information, CBNSs provide a valuable tool for researchers and practitioners tackling complex decision problems.



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