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Bipolar Pythagorean Fuzzy Sets and Their Application in Multi-attribute Decision Making Problems

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  • Wasim Akram Mandal

    (Beldanga D.H.Sr.Madrasah, Beldanga)

Abstract

In this paper, the idea of the bipolar Pythagorean fuzzy sets (BPFSs) and its activities, which is a generalization of fuzzy sets, bipolar fuzzy sets (BFSs), intuitionistic fuzzy sets and bipolar intuitionistic fuzzy sets is proposed, with the goal that it can deal with dubious data all the more flexibly during the process of decision making. The key objective of this research paper has presented another variant of the Pythagorean fuzzy sets so called BPFSs. In bipolar Pythagorean fuzzy sets, membership degrees are satisfying the condition $$0 \le \left( {\mu_{p}^{ + } \left( x \right)} \right)^{2}$$ 0 ≤ μ p + x 2 + $$\left( {v_{p}^{ + } \left( x \right)} \right)^{2} \le 1$$ v p + x 2 ≤ 1 and $$0 \le \left( {\mu_{p}^{ - } \left( x \right)} \right)^{2}$$ 0 ≤ μ p - x 2 + $$\left( {v_{p}^{ - } \left( x \right)} \right)^{2} \le 1$$ v p - x 2 ≤ 1 instead of $$0 \le \left( {\mu_{p} \left( x \right)} \right)^{2}$$ 0 ≤ μ p x 2 + $$\left( {v_{p} \left( x \right)} \right)^{2} \le 1$$ v p x 2 ≤ 1 as is in Pythagorean fuzzy sets and $$0 \le \mu_{p} \left( x \right)$$ 0 ≤ μ p x + $$v_{p} \left( x \right) \le 1$$ v p x ≤ 1 as is in the intuitionistic fuzzy sets. Here, negative membership degree means the certain counter-property comparing to a bipolar Pythagorean fuzzy set. Also, the BPFSs weighted average operator and the BPFSs weighted geometric operator to aggregate the BPFSs is developed here. Further a multi attribute decision making technique is developed and the proposed aggregation operators are used. Finally, a numerical methodology for execution of the proposed system is introduced.

Suggested Citation

  • Wasim Akram Mandal, 2023. "Bipolar Pythagorean Fuzzy Sets and Their Application in Multi-attribute Decision Making Problems," Annals of Data Science, Springer, vol. 10(3), pages 555-587, June.
  • Handle: RePEc:spr:aodasc:v:10:y:2023:i:3:d:10.1007_s40745-020-00315-8
    DOI: 10.1007/s40745-020-00315-8
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    References listed on IDEAS

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    1. Vojo Lakovic, 2020. "Crisis Management of Android Botnet Detection Using Adaptive Neuro-Fuzzy Inference System," Annals of Data Science, Springer, vol. 7(2), pages 347-355, June.
    2. Yong Shi, 2001. "Multiple Criteria and Multiple Constraint Levels Linear Programming:Concepts, Techniques and Applications," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 4000, February.
    3. Totan Garai & Dipankar Chakraborty & Tapan Kumar Roy, 2019. "Multi-objective Inventory Model with Both Stock-Dependent Demand Rate and Holding Cost Rate Under Fuzzy Random Environment," Annals of Data Science, Springer, vol. 6(1), pages 61-81, March.
    4. Chiclana, F. & Herrera-Viedma, E. & Herrera, F. & Alonso, S., 2007. "Some induced ordered weighted averaging operators and their use for solving group decision-making problems based on fuzzy preference relations," European Journal of Operational Research, Elsevier, vol. 182(1), pages 383-399, October.
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    Keywords

    FSs; IFSs; PFs; BFSs; BIFSs; BPFSs;
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