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q-Rung orthopair fuzzy soft Hamacher aggregation operators and their applications in multi-criteria decision making

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Abstract

Soft sets (\({S}_{t}\) S) theory provides a general mechanism for handling uncertainty based on the point of view of parameterization tools. The main theme of this manuscript is to extend the notion of Hamacher operators by establishing an interesting connection between two mathematical concepts \({S}_{t}\) S theory and q-rung orthopair fuzzy sets (q-ROFS). To be specific, we develop some new Hamacher operations for q-rung orthopair fuzzy soft sets (q-ROF \({S}_{t}\) S). In light of these operational laws, we further propose some q-rung orthopair fuzzy soft Hamacher aggregation operators, i.e., q-ROF soft Hamacher averaging and q-ROF soft Hamacher geometric aggregation operators, such as q-ROF soft Hamacher weighted averaging (q-ROF \({S}_{t}\) HWA), q-ROF soft Hamacher ordered weighted averaging (q-ROF \({S}_{t}\) HOWA) and q-ROF soft Hamacher hybrid averaging (q-ROF \({S}_{t}\) HHA) operators. Furthermore, based on Hamacher operator laws, we discuss some geometric aggregation operators such as q-ROF soft Hamacher weighted geometric (q-ROF \({S}_{t}\) HWG), q-ROF soft Hamacher ordered weighted geometric (q-ROF \({S}_{t}\) HOWG) and q-ROF soft Hamacher hybrid geometric (q-ROF \({S}_{t}\) HHG) operators. Meanwhile, the important properties of the developed operators are investigated in detail. Then, a technique for multi-criteria decision making and a stepwise algorithm for decision making are demonstrated by utilizing the proposed approach. Finally, a numerical example for the developed approach is presented and a comparative study of the investigated models with some existing methods is performed. The derived results demonstrate that the investigated models are more effective and useful than the existing approaches.

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References

  • Agarwal M, Biswas KK, Hanmandlu M (2013) Generalized intuitionistic fuzzy soft sets with applications in decision making. Appl Soft Comput 13(8):3552–3566

    Google Scholar 

  • Ali MI (2019) Another view on q-rung orthopair fuzzy sets. Int J Intell Syst 33:2139–2153

    Google Scholar 

  • Ali MI, Feng F, Liu X, Min WK, Shabir M (2009) On some new operations in soft set theory. Comput Math Appl 57:1547–1553

    MathSciNet  Google Scholar 

  • Ali MI, Feng F, Mahmood T, Mahmood I, Faizan H (2019) A graphical method for ranking Atanassov’s intuitionistic fuzzy values using the uncertainty index and entropy. Int J Intell Syst 34(10):2692–2712

    Google Scholar 

  • Arora R (2018) Intuitionistic fuzzy soft aggregation operator based on Einstein norms and its applications in decision-making. In: Int Conf Intell Syst Design Appl. pp 998-1008. Springer, Cham

  • Arora R, Garg H (2018) A robust aggregation operators for multi-criteria decision-making with intuitionistic fuzzy soft set environment. Sci Iranica 25(2):913–942

    Google Scholar 

  • Ashraf S, Rehman N, Hussain A, AlSalman H, Gumaei AH (2021) q-Rung orthopair fuzzy rough Einstein aggregation information-based EDAS method: applications in robotic agrifarming. Comput Intell Neurosci 2021:1

    Google Scholar 

  • Atanassov KT (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96

    MathSciNet  Google Scholar 

  • Chen TY (2007) A note on distances between intuitionistic fuzzy sets and/or interval-valued fuzzy sets based on the Hausdorff metric. Fuzzy Sets Syst 158(22):2523–2525

    MathSciNet  Google Scholar 

  • Chinram R, Hussian A, Mahmood T, Ali MI (2021a) EDAS method for multi-criteria group decision making based on intuitionistic fuzzy rough aggregation operators. IEEE Access 9:10199–11021

    Google Scholar 

  • Chinram R, Hussian A, Ali MI, Mahmood T (2021b) Some geometric aggregation operators under q-Rung orthopair fuzzy soft information with their applications in multi-criteria decision making. IEEE Access 9:31975–31993

    Google Scholar 

  • Darko AP, Liang D (2020) Some q-rung orthopair fuzzy Hamacher aggregation operators and their application to multiple attribute group decision making with modified EDAS method. Eng Appl Artif Intell 87:103259

    Google Scholar 

  • Deschrijver G, Kerre EE (2002) A generalization of operators on intuitionistic fuzzy sets using triangular norms and conorms. Notes on Intuitionistic Fuzzy Sets 8:19–27

    Google Scholar 

  • Deschrijver G, Cornelis C, Kerre EE (2014) On the representation of intuitionistic fuzzy t-norms and t-conorms. IEEE Trans Fuzzy Syst 12:45–61

    Google Scholar 

  • Feng F, Fujita H, Ali MI, Yager RR, Liu X (2018) Another view on generalized intuitionistic fuzzy soft sets and related multi attribute decision making methods. IEEE Trans Fuzzy Syst 27:474–488

    Google Scholar 

  • Garg H (2016) A new generalized Pythagorean fuzzy information aggregation using Einstein operations and its application to decision making. Int J Intell Syst 31(9):886–920

    Google Scholar 

  • Garg H (2017a) Generalized Pythagorean fuzzy geometric aggregation operators using Einstein t-norm and t-conorm for multicriteria decision-making process. Int J Intell Syst 32(6):597–630

    Google Scholar 

  • Garg H (2017b) Confidence levels based Pythagorean fuzzy aggregation operators and its application to decision making process. Comput Math Org Theory 23(4):546–571

    Google Scholar 

  • Garg H (2019) Intuitionistic fuzzy hamacher aggregation operators with entropy weight and their applications to multi-criteria decision-making problems. IJST-T Elec Eng 43(3):597–613

    Google Scholar 

  • Garg H, Arora R (2019) Generalized intuitionistic fuzzy soft power aggregation operator based on t-norm and their application in multicriteria decision-making. Int J Intell Syst 34(2):215–246

    Google Scholar 

  • Guo K, Song Q (2014) On the entropy for Atanassov’s intuitionistic fuzzy sets: An interpretation from the perspective of amount of knowledge. Appl Soft Comput 24:328–340

    Google Scholar 

  • Hamacher H (1978) Uber logische verknupfungen unscharfer aussagen und deren zugehörige bewertungsfunktionen. Progress Cybern Syst Res 3:276–288

    Google Scholar 

  • He X, Yingyu Wu, Dejian Yu, Merigó JM (2017) Exploring the ordered weighted averaging operator knowledge domain: a bibliometric analysis. Int J Intell Syst 32(11):1151–1166

    Google Scholar 

  • Huang JY (2014) Intuitionistic fuzzy Hamacher aggregation operators and their application to multiple attribute decision making. J Intell Fuzzy Syst 27(1):505–513

    MathSciNet  Google Scholar 

  • Hussain A, Mahmood T, Ali MI (2019a) Rough Pythagorean fuzzy ideals in semigroups. Comp Appl Math 38(2):67

    MathSciNet  Google Scholar 

  • Hussain A, Ali MI, Mahmood T (2019b) Covering based q-rung orthopair fuzzy rough set model hybrid with TOPSIS for multi-attribute decision making. J Intell Fuzzy Syst 37:981–993

    Google Scholar 

  • Hussain A, Ali MI, Mahmood T (2019c) Hesitant q-rung orthopair fuzzy aggregation operators with their applications in multi-criteria decision making. Iranian J Fuzzy Syst 17(3):117–134

    MathSciNet  Google Scholar 

  • Hussain A, Ali MI, Mahmood T (2020a) Pythagorean fuzzy soft rough sets and their applications in decision-making. J Taibah Univ Sci 14(1):101–113

    Google Scholar 

  • Hussain A, Ali MI, Mahmood T, Munir M (2020b) q-Rung orthopair fuzzy soft average aggregation operators and their application in multicriteria decision-making. Int J Intell Syst 35(4):571–599

    Google Scholar 

  • Hussian A, Ali MI, Mahmood T, Munir M (2020) Group-based generalized q-rung orthopair average aggregation operators and their application in multi-criteria decision making. Complex Intell Syst 7:1–22

    Google Scholar 

  • Hussain A, Mahmood T, Ali MI, Iampan A (2022) q-Rung orthopair fuzzy soft aggregation operators based on Dombi t-norm and t-conorm with their application in decision making. J Intell Fuzzy Syst 43:1–18

    Google Scholar 

  • Joshi BP, Gegov A (2020) Confidence levels q-rung orthopair fuzzy aggregation operators and its applications to MCDM problems. Int J Intell Syst 35(1):125–149

    Google Scholar 

  • Liang D, Xu Z, Darko AP (2017) Projection model for fusing the information of Pythagorean fuzzy multicriteria group decision making based on geometric Bonferroni mean. Int J Intell Syst 32(9):966–987

    Google Scholar 

  • Liang D, Zhang Y, Xu Z, Darko AP (2018) Pythagorean fuzzy Bonferroni mean aggregation operator and its accelerative calculating algorithm with the multithreading. Int J Intell Syst 33(3):615–633

    Google Scholar 

  • Liu P, Chen SM (2016) Heronian aggregation operators of intuitionistic fuzzy numbers based on the Archimedean t-norm and t-conorm. In: Proc 2016 Int Conf Mach Learn Cybern, Jeju Island, South Korea

  • Liu P, Liu J (2018) Some q-Rung orthopair fuzzy Bonferroni mean operators and their application to multi-attribute group decision making. Int J Intell Syst 33:315–347

    CAS  Google Scholar 

  • Liu P, Wang P (2018) Some q-rung orthopair fuzzy aggregation operators and their applications to multiple attribute decision making. Int J Intell Syst 33:259–280

    Google Scholar 

  • Ma Z, Xu Z (2016) Symmetric Pythagorean fuzzy weighted geometric/averaging operators and their application in multicriteria decision-making problems. Int J Intell Syst 31(12):1198–1219

    Google Scholar 

  • Maji PK, Biswas R, Roy AR (2001a) Fuzzy Soft Sets J Fuzzy Math 9:589–602

    Google Scholar 

  • Maji PK, Biswas R, Roy AR (2001b) Intuitionistic fuzzy soft sets. J Fuzzy Math 9:677–692

    MathSciNet  Google Scholar 

  • Molodtsov D (1999) Soft set theory-first results. Comput Math Appl 37(4–5):19–31

    MathSciNet  Google Scholar 

  • Peng X, Yang Y (2015) Some results for Pythagorean fuzzy sets. Int J Intell Syst 30:1133–1160

    Google Scholar 

  • Peng X, Dai J, Garg H (2018) Exponential operation and aggregation operator for q-rung orthopair fuzzy set and their decision-making method with a new score function. Int J Intell Syst 33(11):2255–2282

    Google Scholar 

  • Riaz M, Farid HMA, Karaaslan F, Hashmi MR (2020) Some q-rung orthopair fuzzy hybrid aggregation operators and TOPSIS method for multi-attribute decision-making. J Intell Fuzzy Syst 39(1):1227–1241

    Google Scholar 

  • Roychowdhury S, Wang BH (1998) On generalized Hamacher families of triangular operators. Int J Approx Reas 19:419–439

    MathSciNet  Google Scholar 

  • Wang Y, Hussain A, Mahmood T, Ali MI, Wu H, Jin Y (2020) Decision making based on q-rung orthopair fuzzy soft rough sets. Math Probl Eng 2020:1–21

    MathSciNet  Google Scholar 

  • Wei GW (2017) Pythagorean fuzzy interaction aggregation operators and their application to multiple attribute decision making. J Intell Fuzzy Syst 33(4):2119–2132

    CAS  Google Scholar 

  • Wei GW (2019) Pythagorean fuzzy Hamacher power aggregation operators in multiple attribute decision making. Fundam Inform 166(1):57–85

    MathSciNet  Google Scholar 

  • Wei G, Lu M (2018) Pythagorean fuzzy power aggregation operators in multiple attribute decision making. Int J Intell Syst 33:169–186

    Google Scholar 

  • Wei G, Gao H, Wei Y (2018) Some q-rung orthopair fuzzy Heronian mean operators in multiple attribute decision making. Int J Intell Syst 33(7):1426–1458

    Google Scholar 

  • Wei G, Wei C, Wang J, Gao H, Wei Y (2019) Some q-rung orthopair fuzzy Maclaurin symmetric mean operators and their applications to potential evaluation of emerging technology commercialization. Int J Intell Syst 34(1):50–81

    Google Scholar 

  • Wu SJ, Wei GW (2017) Pythagorean fuzzy Hamacher aggregation operators and their application to multiple attribute decision making. Int J Knowledge-Based Intell Eng Syst 21(3):189–201

    Google Scholar 

  • Xu ZS (2007) Intuitionistic fuzzy aggregation operators. IEEE Trans Fuzzy Syst 15(6):1179–1187

    Google Scholar 

  • Xu Z, Yager RR (2006) Some geometric aggregation operators based on intuitionistic fuzzy sets. Int J Gen Syst 35(4):417–433

    MathSciNet  Google Scholar 

  • Xu Z, Yager RR (2010) Power-geometric operators and their use in group decision making. IEEE Trans Fuzzy Syst 18(1):94–105

    Google Scholar 

  • Yager RR (2001) The power average operator. IEEE T Syst Man Cy a 31(6):724–731

    Google Scholar 

  • Yager, R.R. Pythagorean fuzzy subsets. Proceedings of the Joint IFSA World Congress and NAFIPS Annual Meeting Edmonton Canada. 2013, 57–61

  • Yager RR (2014) Pythagorean membership grades in multicriteria decision making. IEEE Trans Fuzzy Syst 22:958–965

    Google Scholar 

  • Yager RR (2016) Generalized orthopair fuzzy sets. IEEE Trans Fuzzy Syst 25:1222

    Google Scholar 

  • Yang W, Pang Y (2019) New q-rung orthopair fuzzy partitioned Bonferroni mean operators and their application in multiple attribute decision making. Int J Intell Syst 34(3):439–476

    Google Scholar 

  • Yu D (2012) Group decision making based on generalized intuitionistic fuzzy prioritized geometric operator. Int J Intell Syst 27(7):635–661

    Google Scholar 

  • Yu D (2013) Multi-criteria decision making based on generalized prioritized aggregation operators under intuitionistic fuzzy environment. Int J Fuzzy Syst 15(1):47–54

    MathSciNet  Google Scholar 

  • Yu D (2015) A scientometrics review on aggregation operator research. Scientometrics 105(1):115–133

    Google Scholar 

  • Yu D, Wang W, Zhang W, Zhang S (2018) A bibliometric analysis of research on multiple criteria decision making. Curr Sci 114:747–758

    Google Scholar 

  • Yu D, Zeshui Xu, Pedrycz W (2020) Bibliometric analysis of rough sets research. Appl Soft Comput 94:106467

    Google Scholar 

  • Yu D, Fang A, Zeshui X (2023) The knowledge trajectory and thematic evolution of the rough sets research: a main path and scientific mapping analysis. Appl Soft Comput 143:110364

    Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353

    Google Scholar 

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Acknowledgements

The authors would like to thank the Editor-in-Chief, an Associate Editor, and the anonymous referees for detailed and valuable comments which helped to improve this manuscript.

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Correspondence to Azmat Hussian or Vassilis C. Gerogiannis.

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Communicated by Junsheng Qiao.

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Hussian, A., Mahmood, T., Ali, M.I. et al. q-Rung orthopair fuzzy soft Hamacher aggregation operators and their applications in multi-criteria decision making. Comp. Appl. Math. 43, 22 (2024). https://doi.org/10.1007/s40314-023-02477-6

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