Research article

Algebraic structures of picture fuzzy level operators with metric properties

  • Published: 10 October 2026
  • MSC : 03E72, 06B23, 20M14, 54E35

  • This paper investigates the algebraic structure of picture fuzzy level operators. The concept of level subsets for picture fuzzy sets was introduced by Kankaew et al. [1] in the context of UP (BCC)-algebras, where they defined the upper and lower level subsets $ \mathcal{U}_\mu(t) $, $ \mathcal{U}_\eta(t) $, and $ \mathcal{L}_\nu(t) $. Building upon this foundational work, we define picture fuzzy level operators $ L_{\alpha, \beta, \gamma} $ and investigate their algebraic properties. Let $ \mathcal{L} = \{ L_{\alpha, \beta, \gamma} : \alpha, \beta, \gamma \in [0, 1], \; 0 \le \alpha+\beta+\gamma \le 1 \} $ denote the admissible set of all picture fuzzy level operators, and let $ \overline{\mathcal{L}} = \{ L_{\alpha, \beta, \gamma} : \alpha, \beta, \gamma \in [0, 1] \} $ denote the extended operator space obtained by dropping the constraint $ \alpha+\beta+\gamma \le 1 $. We define a partial order $ \preceq $ on $ \overline{\mathcal{L}} $ by componentwise order with $ \gamma $ reversed. We prove that $ (\overline{\mathcal{L}}, \preceq) $ is a poset, with $ \mathcal{L} $ as a sub-poset. We introduce the meet $ \sqcap $ and join $ \sqcup $ operations and show that $ (\overline{\mathcal{L}}, \sqcap, \sqcup) $ forms a distributive lattice, and moreover a complete lattice. The admissible set $ \mathcal{L} $ is characterized as closed under meet but not under join. We define composition $ \circ $ of level operators and prove that $ (\overline{\mathcal{L}}, \circ) $ forms a commutative idempotent monoid with identity $ L_{0, 0, 1} $, with the interesting property that composition coincides with the join operation. We investigate inverse operators, proving that only the identity operator has a true inverse, and introduce dual operators satisfying natural duality properties. We establish metric structures, including Chebyshev, Manhattan, and Euclidean distances on $ \overline{\mathcal{L}} $. Finally, we provide a geometric interpretation via the operator simplex—a tetrahedral representation in $ \mathbb{R}^3 $ that visualizes the admissible set of level operators. This work provides a systematic algebraic and geometric framework for understanding picture fuzzy level operators.

    Citation: Ümit Deniz. Algebraic structures of picture fuzzy level operators with metric properties[J]. AIMS Mathematics, 2026, 11(10): 32894-32919. doi: 10.3934/math.20261290

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  • This paper investigates the algebraic structure of picture fuzzy level operators. The concept of level subsets for picture fuzzy sets was introduced by Kankaew et al. [1] in the context of UP (BCC)-algebras, where they defined the upper and lower level subsets $ \mathcal{U}_\mu(t) $, $ \mathcal{U}_\eta(t) $, and $ \mathcal{L}_\nu(t) $. Building upon this foundational work, we define picture fuzzy level operators $ L_{\alpha, \beta, \gamma} $ and investigate their algebraic properties. Let $ \mathcal{L} = \{ L_{\alpha, \beta, \gamma} : \alpha, \beta, \gamma \in [0, 1], \; 0 \le \alpha+\beta+\gamma \le 1 \} $ denote the admissible set of all picture fuzzy level operators, and let $ \overline{\mathcal{L}} = \{ L_{\alpha, \beta, \gamma} : \alpha, \beta, \gamma \in [0, 1] \} $ denote the extended operator space obtained by dropping the constraint $ \alpha+\beta+\gamma \le 1 $. We define a partial order $ \preceq $ on $ \overline{\mathcal{L}} $ by componentwise order with $ \gamma $ reversed. We prove that $ (\overline{\mathcal{L}}, \preceq) $ is a poset, with $ \mathcal{L} $ as a sub-poset. We introduce the meet $ \sqcap $ and join $ \sqcup $ operations and show that $ (\overline{\mathcal{L}}, \sqcap, \sqcup) $ forms a distributive lattice, and moreover a complete lattice. The admissible set $ \mathcal{L} $ is characterized as closed under meet but not under join. We define composition $ \circ $ of level operators and prove that $ (\overline{\mathcal{L}}, \circ) $ forms a commutative idempotent monoid with identity $ L_{0, 0, 1} $, with the interesting property that composition coincides with the join operation. We investigate inverse operators, proving that only the identity operator has a true inverse, and introduce dual operators satisfying natural duality properties. We establish metric structures, including Chebyshev, Manhattan, and Euclidean distances on $ \overline{\mathcal{L}} $. Finally, we provide a geometric interpretation via the operator simplex—a tetrahedral representation in $ \mathbb{R}^3 $ that visualizes the admissible set of level operators. This work provides a systematic algebraic and geometric framework for understanding picture fuzzy level operators.



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    [1] P. Kankaew, S. Yuphaphin, N. Lapo, R. Chinram, P. Julatha, A. Iampan, Characteristic picture fuzzy sets and level subsets in UP (BCC)-algebras, Int. J. Anal. Appl., 21 (2023), 75. https://doi.org/10.28924/2291-8639-21-2023-75 doi: 10.28924/2291-8639-21-2023-75
    [2] L. A. Zadeh, Fuzzy sets, Inform. Control, 8 (1965), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X doi: 10.1016/S0019-9958(65)90241-X
    [3] A. Rosenfeld, Fuzzy groups, J. Math. Anal. Appl., 35 (1971), 512–517. https://doi.org/10.1016/0022-247x(71)90199-5 doi: 10.1016/0022-247x(71)90199-5
    [4] K. T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Sets Syst., 20 (1986), 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3 doi: 10.1016/S0165-0114(86)80034-3
    [5] K. T. Atanassov, New operations defined over the intuitionistic fuzzy sets, Fuzzy Sets Syst., 61 (1994), 137–142. https://doi.org/10.1016/0165-0114(94)90229-1 doi: 10.1016/0165-0114(94)90229-1
    [6] H. Bustince, P. Burillo, Vague sets are intuitionistic fuzzy sets, Fuzzy Sets Syst., 79 (1996), 403–405. https://doi.org/10.1016/0165-0114(95)00154-9 doi: 10.1016/0165-0114(95)00154-9
    [7] P. K. Sharma, Homomorphism of intuitionistic fuzzy groups, Int. Math. Forum, 6 (2011), 3169–3178.
    [8] R. Biswas, Fuzzy subgroups and anti-fuzzy subgroups, Fuzzy Sets Syst., 35 (1990), 121–124. https://doi.org/10.1016/0165-0114(90)90025-2 doi: 10.1016/0165-0114(90)90025-2
    [9] B. C. Cuong, Picture fuzzy sets, J. Comput. Sci. Cybernet., 30 (2014), 409–420. https://doi.org/10.15625/1813-9663/30/4/5032 doi: 10.15625/1813-9663/30/4/5032
    [10] G. Wei, Some cosine similarity measures for picture fuzzy sets and their applications to strategic decision making, Informatica, 28 (2017), 547–564. https://doi.org/10.15388/Informatica.2017.144 doi: 10.15388/Informatica.2017.144
    [11] S. Mufazzal, N. Z. Khan, S. M. Muzakkir, A. N. Siddiquee, Z. A. Khan, A new fuzzy multi-criteria decision-making method based on proximity index value, J. Ind. Prod. Eng., 39 (2022), 42–58. https://doi.org/10.1080/21681015.2021.1958935 doi: 10.1080/21681015.2021.1958935
    [12] F. Smarandache, Neutrosophy: neutrosophic probability, set, and logic: analytic synthesis & synthetic analysis, Rehoboth: American Research Press, 1998.
    [13] P. Majumdar, S. K. Samanta, On similarity and entropy of neutrosophic sets, J. Intell. Fuzzy Syst., 26 (2014), 1245–1252. https://doi.org/10.3233/IFS-130810 doi: 10.3233/IFS-130810
    [14] F. Smarandache, Introduction to neutrosophy, neutrosophic set, neutrosophic probability, neutrosophic statistics and their applications to decision making, In: Neutrosophic paradigms: advancements in decision making and statistical analysis, studies in fuzziness and soft computing, Cham: Springer, 2025, 3–21. https://doi.org/10.1007/978-3-031-78505-4_1
    [15] M. Ali, F. Smarandache, Complex neutrosophic set, Neural Comput. Appl., 28 (2017), 1817–1834. https://doi.org/10.1007/s00521-015-2154-y doi: 10.1007/s00521-015-2154-y
    [16] F. Smarandache, Plithogeny, plithogenic set, logic, probability and statistics: a short review, J. Comput. Cogn. Eng., 1 (2022), 47–50. https://doi.org/10.47852/bonviewJCCE2202191 doi: 10.47852/bonviewJCCE2202191
    [17] Y. B. Jun, S. Z. Song, S. J. Kim, Length-fuzzy subalgebras in BCK/BCI-algebras, Mathematics, 6 (2018), 11. https://doi.org/10.3390/math6010011 doi: 10.3390/math6010011
    [18] F. Kutlu Gündogdu, C. Kahraman, Spherical fuzzy sets and spherical fuzzy TOPSIS method, J. Intell. Fuzzy Syst., 36 (2019), 337–352. https://doi.org/10.3233/JIFS-181401 doi: 10.3233/JIFS-181401
    [19] R. R. Yager, Generalized orthopair fuzzy sets, IEEE Trans. Fuzzy Syst., 25 (2017), 1222–1230. https://doi.org/10.1109/TFUZZ.2016.2604005 doi: 10.1109/TFUZZ.2016.2604005
    [20] W. A. Khan, K. Faiz, A. Taouti, Bipolar picture fuzzy sets and relations with applications, Songklanakarin J. Sci. Technol., 44 (2022), 987–999. https://doi.org/10.14456/sjst-psu.2022.131 doi: 10.14456/sjst-psu.2022.131
    [21] T. Mahmood, U. Rehman, J. Ahmmad, Complex picture fuzzy N-soft sets and their decision-making algorithm, Soft Comput., 25 (2021), 13657–13678. https://doi.org/10.1007/s00500-021-06108-2 doi: 10.1007/s00500-021-06108-2
    [22] W. Nakkhasen, A. Chada, T. Jodnok, $m$-polar picture fuzzy bi-ideals and their applications in semigroups, Symmetry, 17 (2025), 2051. https://doi.org/10.3390/sym17122051 doi: 10.3390/sym17122051
    [23] M. K. Gunjan, A. K. Adak, W. Ali, Picture fuzzy subalgebras and ideals in Sheffer stroke UP-algebras, J. Adv. Math. Com. Sci., 41 (2026), 49–60. https://doi.org/10.9734/jamcs/2026/v41i22099 doi: 10.9734/jamcs/2026/v41i22099
    [24] G. Deschrijver, E. E. Kerre, On the relationship between some extensions of fuzzy set theory, Fuzzy Sets Syst., 133 (2003), 227–235. https://doi.org/10.1016/S0165-0114(02)00127-6 doi: 10.1016/S0165-0114(02)00127-6
    [25] P. Bharathi, Picture fuzzy lattices, Adv. Appl. Math. Sci., 18 (2019), 1203–1207.
    [26] M. K. Hasan, Picture fuzzy lattices, ideals and homomorphism, Trans. Fuzzy Sets Syst., 4 (2025), 14–33. https://doi.org/10.71602/tfss.2025.1128335 doi: 10.71602/tfss.2025.1128335
    [27] G. Birkhoff, Lattice theory, Providence: American Mathematical Society, 1967.
    [28] G. Grätzer, General lattice theory, Basel: Birkhäuser Verlag, 1978. https://doi.org/10.1007/978-3-0348-7633-9
    [29] B. A. Davey, H. A. Priestley, Introduction to lattices and order, Cambridge: Cambridge University Press, 2002. https://doi.org/10.1017/CBO9780511809088
    [30] J. M. Howie, Fundamentals of semigroup theory, Oxford: Oxford University Press, 1995. https://doi.org/10.1093/oso/9780198511946.001.0001
    [31] J. N. Mordeson, D. S. Malik, N. Kuroki, Studies in fuzziness and soft computing, In: Fuzzy semigroups, Heidelberg: Springer, 2003. https://doi.org/10.1007/978-3-540-37125-0
    [32] W. Rudin, Principles of mathematical analysis, New York: McGraw-Hill, 1976.
    [33] W. A. Sutherland, Introduction to metric and topological spaces, Oxford: Oxford University Press, 2009.
    [34] K. Javed, A. Asif, E. Savas, A note on orthogonal fuzzy metric space, its properties, and fixed point theorems, J. Funct. Spaces, 2022 (2022), 5863328. https://doi.org/10.1155/2022/5863328 doi: 10.1155/2022/5863328
    [35] E. F. Okumuş, S. Yamak, Picture fuzzy ideals in semigroups under the Type-3 order: bi-ideals, quasi-ideals, and interior ideals, Black Sea J. Eng. Sci., 9 (2026), 1607–1612. https://doi.org/10.34248/bsengineering.1925455 doi: 10.34248/bsengineering.1925455
    [36] M. Riaz, H. M. A. Farid, Hierarchical medical diagnosis approach for COVID-19 based on picture fuzzy fairly aggregation operators, Int. J. Biomath., 16 (2023), 2250075. https://doi.org/10.1142/S1793524522500759 doi: 10.1142/S1793524522500759
    [37] H. Günay Akdemir, H. Gonce Kocken, N. Kara, Modeling risk attitudes in picture fuzzy multi-objective linear programming with chance constraints, Inf. Sci., 734 (2026), 123003. https://doi.org/10.1016/j.ins.2025.123003 doi: 10.1016/j.ins.2025.123003
    [38] Z. Ali, T. Mahmood, M. S. Yang, Aczel–Alsina power aggregation operators for complex picture fuzzy (CPF) sets with application in CPF multi-attribute decision making, Symmetry, 15 (2023), 651. https://doi.org/10.3390/sym15030651 doi: 10.3390/sym15030651
    [39] U. Ali, J. Li, T. Senapati, S. A. Edalatpanah, S. Duleba, S. Moslem, A hybrid decision-making model in a complex Fermatean picture fuzzy environment with application to emergency management, Complex Intell. Syst., 12 (2026), 15. https://doi.org/10.1007/s40747-025-02112-3 doi: 10.1007/s40747-025-02112-3
    [40] F. Smarandache, Introduction to SuperHyperAlgebra and neutrosophic SuperHyperAlgebra, J. Algebraic Hyperstructures Log. Algebras, 3 (2022), 17–24. https://doi.org/10.52547/HATEF.JAHLA.3.2.2 doi: 10.52547/HATEF.JAHLA.3.2.2
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