Research article Special Issues

Averaging aggregation operators under the environment of q-rung orthopair picture fuzzy soft sets and their applications in MADM problems

  • Received: 31 October 2022 Revised: 04 February 2023 Accepted: 06 February 2023 Published: 10 February 2023
  • MSC : 60L70, 68N17

  • q-Rung orthopair fuzzy soft set handles the uncertainties and vagueness by membership and non-membership degree with attributes, here is no information about the neutral degree so to cover this gap and get a generalized structure, we present hybrid of picture fuzzy set and q-rung orthopair fuzzy soft set and initiate the notion of q-rung orthopair picture fuzzy soft set, which is characterized by positive, neutral and negative membership degree with attributes. The main contribution of this article is to investigate the basic operations and some averaging aggregation operators like q-rung orthopair picture fuzzy soft weighted averaging operator and q-rung orthopair picture fuzzy soft order weighted averaging operator under the environment of q-rung orthopair picture fuzzy soft set. Moreover, some fundamental properties and results of these aggregation operators are studied, and based on these proposed operators we presented a stepwise algorithm for MADM by taking the problem related to medical diagnosis under the environment of q-rung orthopair picture fuzzy soft set and finally, for the superiority we presented comparison analysis of proposed operators with existing operators.

    Citation: Sumbal Ali, Asad Ali, Ahmad Bin Azim, Ahmad ALoqaily, Nabil Mlaiki. Averaging aggregation operators under the environment of q-rung orthopair picture fuzzy soft sets and their applications in MADM problems[J]. AIMS Mathematics, 2023, 8(4): 9027-9053. doi: 10.3934/math.2023452

    Related Papers:

  • q-Rung orthopair fuzzy soft set handles the uncertainties and vagueness by membership and non-membership degree with attributes, here is no information about the neutral degree so to cover this gap and get a generalized structure, we present hybrid of picture fuzzy set and q-rung orthopair fuzzy soft set and initiate the notion of q-rung orthopair picture fuzzy soft set, which is characterized by positive, neutral and negative membership degree with attributes. The main contribution of this article is to investigate the basic operations and some averaging aggregation operators like q-rung orthopair picture fuzzy soft weighted averaging operator and q-rung orthopair picture fuzzy soft order weighted averaging operator under the environment of q-rung orthopair picture fuzzy soft set. Moreover, some fundamental properties and results of these aggregation operators are studied, and based on these proposed operators we presented a stepwise algorithm for MADM by taking the problem related to medical diagnosis under the environment of q-rung orthopair picture fuzzy soft set and finally, for the superiority we presented comparison analysis of proposed operators with existing operators.



    加载中


    [1] L. A. Zadeh, Fuzzy sets, Inf. Control, 8 (1965), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X doi: 10.1016/S0019-9958(65)90241-X
    [2] L. A. Zadeh, The concept of a linguistic variable and its application to approximate reasoning-I, Inform. Sci., 8 (1975), 199–249. https://doi.org/10.1016/0020-0255(75)90036-5 doi: 10.1016/0020-0255(75)90036-5
    [3] Q. Song, A. Kandel, M. Schneider, Parameterized fuzzy operators in fuzzy decision-making, Int. J. Intell. Syst., 18 (2003), 971–987. https://doi.org/10.1002/int.10124 doi: 10.1002/int.10124
    [4] H. Zhao, Z. Xu, M. Ni, S. Liu, Generalized aggregation operators for intuitionistic fuzzy sets, Int. J. Intell. Syst., 25 (2010), 1–30. https://doi.org/10.1002/int.20386 doi: 10.1002/int.20386
    [5] C. Tan, Generalized intuitionistic fuzzy geometric aggregation operator and its application to multi-criteria group decision-making, Soft Comput., 15 (2011), 867–876. doi: 10.1007/s00500-010-0554-6
    [6] C. Tan, W. Yi, X. Chen, Generalized intuitionistic fuzzy geometric aggregation operators and their application to multi-criteria decision making, J. Oper. Res. Soc., 66 (2015), 1919–19. https://doi.org/10.1057/jors.2014.104 doi: 10.1057/jors.2014.104
    [7] B. C. Cuong, Picture fuzzy sets, J. Comput. Sci. Cybern., 30 (2014), 409. https://doi.org/10.15625/1813-9663/30/4/5032 doi: 10.15625/1813-9663/30/4/5032
    [8] H. Garg, Some picture fuzzy aggregation operators and their applications to multi-criteria decision-making, Arab. J. Sci. Eng., 42 (2017), 5275–5290. https://doi.org/10.1007/s13369-017-2625-9 doi: 10.1007/s13369-017-2625-9
    [9] G. Wei, Picture fuzzy aggregation operators and their application to multiple attribute decision-making, J. Intell. Fuzzy Syst., 33 (2017), 713–724. https://doi.org/10.3233/JIFS-161798 doi: 10.3233/JIFS-161798
    [10] S. Khan, S. Abdullah, S. Ashraf, Picture fuzzy aggregation information based on Einstein operations and their application in decision-making, Math. Sci., 13 (2019), 213–229. https://doi.org/10.1007/s40096-019-0291-7 doi: 10.1007/s40096-019-0291-7
    [11] C. Jana, T. Senapati, M. Pal, R. R. Yager, Picture fuzzy Dombi aggregation operators: Application to MADM process, Appl. Soft Comput., 74 (2019), 99–109. https://doi.org/10.1016/j.asoc.2018.10.021 doi: 10.1016/j.asoc.2018.10.021
    [12] R. R. Yager, Pythagorean fuzzy subsets, In 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), IEEE, Edmonton, Canada, 2013, 57–61. https://doi.org/10.1109/IFSA-NAFIPS.2013.6608375
    [13] R. R. Yager, Pythagorean membership grades in multi-criteria decision making, IEEE Trans. Fuzzy Syst., 22 (2014), 958–965. https://doi.org/10.1109/TFUZZ.2013.2278989 doi: 10.1109/TFUZZ.2013.2278989
    [14] R. R. Yager, A. M. Abbasov, Pythagorean membership grades, complex numbers, and decision making, Int. J. Intell. Syst., 2 (2014), 436–452. https://doi.org/10.1002/int.21584 doi: 10.1002/int.21584
    [15] P. Liu, P. Wang, Some q-rung orthopair fuzzy aggregation operators and their applications to multiple-attribute decision-making, Int. J. Intell. Syst., 33 (2018), 259–280. https://doi.org/10.1002/int.21927 doi: 10.1002/int.21927
    [16] P. Liu, J. Liu, some q-rung orthopair fuzzy Bonferroni mean operators and their application to multi-attribute group decision-making, Int. J. Intell. Syst., 33 (2018), 315–347. https://doi.org/10.1002/int.21933 doi: 10.1002/int.21933
    [17] P. Liu, S. M. Chen, P. Wang, Multiple-attribute group decision-making based on q-rung orthopair fuzzy power maclurin symmetric mean operators, IEEE Trans. Syst. Man Cybern. Syst., 2018, 1–16. https://doi.org/10.1109/TSMC.2018.2852948 doi: 10.1109/TSMC.2018.2852948
    [18] C. Jana, G. Muhiuddin, M. Pal, Some Dombi aggregation of q-rung orthopair fuzzy numbers in multiple-attribute decision-making, Int. J. Intell. Syst., 34 (2019), 3220–3240. https://doi.org/10.1002/int.22191 doi: 10.1002/int.22191
    [19] H. Garg, S. M. Chen, Multi-attribute group decision-making based on neutrality aggregation operators of q-rung orthopair fuzzy sets, Inf. Sci., 517 (2020), 427–447. https://doi.org/10.1016/j.ins.2019.11.035 doi: 10.1016/j.ins.2019.11.035
    [20] R. R. Yager, Generalized orthopair fuzzy sets, IEEE T. Fuzzy Syst., 25 (2016), 1222–1230. https://doi.org/10.1109/TFUZZ.2016.2604005 doi: 10.1109/TFUZZ.2016.2604005
    [21] D. Molodtsov, Soft set theory-first results, Comput. Math. Appl., 37 (1999), 19–31. https://doi.org/10.1016/S0898-1221(99)00056-5 doi: 10.1016/S0898-1221(99)00056-5
    [22] P. K. Maji, R. Biswas, A. R. Roy, Fuzzy soft sets, J. Fuzzy Math., 9 (2001), 589–602.
    [23] P. Maji, R. Biswas, A. Roy, Intuitionistic fuzzy soft sets, J. Fuzzy Math., 9 (2001), 677–692.
    [24] A. Hussain, M. I. Ali, T. Mahmood, M. Munir, q-Rung orthopair fuzzy soft average aggregation operators and their application in multicriteria decision-making, Int. J. Intell. Syst., 35 (2020), 571–599. https://doi.org/10.1002/int.22217 doi: 10.1002/int.22217
    [25] F. Smarandache, A unifying field in logics neutrosophy: Neutrosophic probability, set and logic, American Research Press, Rehoboth, 1999.
    [26] Z. S. Xu, Intuitionistic fuzzy aggregation operators, IEEE Trans Fuzzy Syst., 15 (2007), 1179–1187. https://doi.org/10.1109/TFUZZ.2006.890678 doi: 10.1109/TFUZZ.2006.890678
    [27] R. Arora, H. Garg, A robust aggregation operators for multi-criteria decision-making with intuitionistic fuzzy soft set environment, Sci. Iran., 25 (2018), 913–942. https://doi.org/10.24200/sci.2017.4433 doi: 10.24200/sci.2017.4433
    [28] R. M. Zulqarnain, X. L. Xin, H. Garg, W. A. Khan, Aggregation operators of Pythagorean fuzzy soft sets with their application for green supplier chain management, J. Intell. Fuzzy Syst., 40 (2021), 5545–5563. https://doi.org/10.3233/JIFS-202781 doi: 10.3233/JIFS-202781
    [29] K. T. Atanassov, Intuitionistic fuzzy sets, Fuzzy Set. Syst., 20 (1986), 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3 doi: 10.1016/S0165-0114(86)80034-3
    [30] B. P. Joshi, A. Singh, P. K. Bhatt, K. S. Vaisla, Interval valued q-rung orthopair fuzzy sets and their properties, J. Intell. Fuzzy Syst., 35 (2018), 5225–5230. https://doi.org/10.3233/JIFS-169806 doi: 10.3233/JIFS-169806
    [31] K. Hayat, M. S. Raja, E. Lughofer, N. Yaqoob, New group-based generalized interval-valued q-rung orthopair fuzzy soft aggregation operators and their applications in sports decision-making problems, Comput. Appl. Math., 42 (2023), 1–28. https://doi.org/10.1007/s40314-022-02130-8 doi: 10.1007/s40314-022-02135-3
    [32] X. Yang, K. Hayat, M. S. Raja, N. Yaqoob, C. Jana, Aggregation and interaction aggregation soft operators on interval-valued q-rung orthopair fuzzy soft environment and application in automation company evaluation, IEEE Access, 10 (2022), 91424–91444. https://doi.org/10.1109/ACCESS.2022.3202211 doi: 10.1109/ACCESS.2022.3202211
    [33] K. Hayat, R. A. Shamim, H. Al Salman, A. Gumaei, X. P. Yang, M. A. Akbar, Group Generalized q-Rung orthopair fuzzy soft sets: New aggregation operators and their applications, Math. Probl. Eng., 2021 (2021). https://doi.org/10.1155/2021/5672097 doi: 10.1155/2021/5672097
    [34] I. Deli, N. Çağman, Intuitionistic fuzzy parameterized soft set theory and its decision making, Appl. Soft Comput., 28 (2015), 109–113. https://doi.org/10.1016/j.asoc.2014.11.053 doi: 10.1016/j.asoc.2014.11.053
    [35] I. Deli, A TOPSIS method by using generalized trapezoidal hesitant fuzzy numbers and application to a robot selection problem, J. Intell. Fuzzy Syst., 38 (2020), 779–793. https://doi.org/10.3233/JIFS-179448 doi: 10.3233/JIFS-179448
    [36] I. Deli, S. Broumi, Neutrosophic soft matrices and NSM-decision making, J. Intell. Fuzzy Syst., 28 (2015), 2233–2241. https://doi.org/10.3233/IFS-141505 doi: 10.3233/IFS-141505
    [37] M. Akram, G. Shahzadi, J. C. R. Alcantud, Multi-attribute decision-making with q-rung picture fuzzy information, Granular Comput., 7 (2022), 197–215. https://doi.org/10.1007/s41066-021-00260-8 doi: 10.1007/s41066-021-00260-8
    [38] M. Akram, M. Shabir, A. N. Al-Kenani, J. C. R. Alcantud, Hybrid decision-making frameworks under complex spherical fuzzy N-soft sets, J. Math., 2021 (2021), 1–46. https://doi.org/10.1155/2021/5563215 doi: 10.1155/2021/5563215
    [39] M. Akram, A. Luqman, J. C. R. Alcantud, Risk evaluation in failure modes and effects analysis: hybrid TOPSIS and ELECTRE I solutions with Pythagorean fuzzy information, Neural Comput. Appl., 33 (2021), 5675–5703. https://doi.org/10.1007/s00521-020-05350-3 doi: 10.1007/s00521-020-05350-3
    [40] M. Akram, F. Wasim, J. C. R. Alcantud, A. N. Al-Kenani, Multi-criteria optimization technique with complex Pythagorean fuzzy n-soft information, Int. J. Comput. Intel. Syst., 14 (2021), 1–24. https://doi.org/10.1007/s44196-021-00008-x doi: 10.1007/s44196-021-00008-x
    [41] M. Akram, M. Amjad, J. C. R. Alcantud, G. Santos-García, Complex Fermatean fuzzy N-soft sets: A new hybrid model with applications, J. Amb. Intel. Hum. Comp., 14 (2022), 1–34. https://doi.org/10.1007/s12652-021-03629-4 doi: 10.1007/s12652-021-03629-4
  • Reader Comments
  • © 2023 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(809) PDF downloads(68) Cited by(0)

Article outline

Figures and Tables

Figures(3)  /  Tables(12)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog