Skip to main content
Log in

IFP-intuitionistic multi fuzzy N-soft set and its induced IFP-hesitant N-soft set in decision-making

  • Original Research
  • Published:
Journal of Ambient Intelligence and Humanized Computing Aims and scope Submit manuscript

Abstract

Intuitionistic fuzzy sets (IFSs) can effectively represent and simulate the uncertainty and diversity of judgment information offered by decision-makers (DMs). In comparison to fuzzy sets (FSs), IFSs are highly beneficial for expressing vagueness and uncertainty more accurately. As a result, in this paper, we offer an approach for solving group decision-making problems (DMPs) with intuitionistic fuzzy parameterized (IFP) intuitionistic multi fuzzy N-soft set of dimension q (briefly, IFPIMFNSS) by introducing its induced IFP-hesitant N-soft set (IFPHNSS) as an extension of the multi-fuzzy N-soft set (MFNSS) based decision-making method (DMM). MFNSS is a fantastic and useful tool to deal with DMPs, but it has some limitations to solve group DMPs, but the constructed method in this paper is very advantageous for group-DMPs. To demonstrate the applicability of our methodology in practical situations, some examples are used, and also, we have compared the ranking performances of the proposed method with the Fatimah-Alcantud method. Finally, we bring the paper to a conclusion and our future work.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Abbreviations

DM:

Decision-maker

DMM:

Decision-making method

DMP:

Decision-making problem

IFPIMFNSS :

IFP-intuitionistic multi fuzzy N-soft set of dimension q

FSS:

Fuzzy soft set

FST:

Fuzzy set theory

HFS:

Hesitant fuzzy set

HNSS:

Hesitant N soft set

HNT:

Hesitant N tuples

IFPHNSS :

IFP-hesitant N-soft set of dimension q

IFS:

Intuitionistic fuzzy set

IFSS:

Intuitionistic fuzzy soft set

IVFS:

Interval-valued fuzzy set

IVFSS:

Interval-valued fuzzy soft set

IMFS:

Intuitionistic multi fuzzy set

MFNSS:

Multi-fuzzy N-soft set

NSS:

N-soft set

SST:

Soft set theory

References

  • Abdulkareem KH, Arbaiy N, Zaidan AA et al (2020a) A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis methods. Neural Comput Appl. https://doi.org/10.1007/s00521-020-05020-4

    Article  Google Scholar 

  • Abdulkareem KH, Arbaiy N, Zaidan AA et al (2020b) A novel multiperspective benchmarking framework for selecting image dehazing intelligent algorithms based on BWM and group VIKOR techniques. Int J Inf Technol Decis Mak 19(3):909–957

    Google Scholar 

  • Akram M, Adeel A (2019) TOPSIS approach for MAGDM based on interval-valued hesitant fuzzy N-soft environment. Int J Fuzzy Syst 21(3):993–1009

    Google Scholar 

  • Akram M, Adeel A, Alcantud JCR (2018) Fuzzy N-soft sets: a novel model with applications. J Intell Fuzzy Syst 35(4):4757–4771

    Google Scholar 

  • Akram M, Adeel A, Alcantud JCR (2019a) Group decision-making methods based on hesitant N-soft sets. Expert Syst Appl 115:95–105

    Google Scholar 

  • Akram M, Adeel A, Alcantud JCR (2019b) Hesitant fuzzy N-soft sets: A new model with applications in decision-making. J Intell Fuzzy Syst 36(6):6113–6127

    Google Scholar 

  • Akram M, Ali G, Alcantud JCR (2019c) New decision-making hybrid model: intuitionistic fuzzy N-soft rough sets. Soft Comput 23(20):9853–9868

    MATH  Google Scholar 

  • Akram M, Ali G, Alcantud JCR, Fatimah F (2020) Parameter reductions in N-soft sets and their applications in decision-making. Expert Syst (in press)

  • Alcantud JCR (2020) Soft open bases and a novel construction of soft topologies from bases for topologies. Mathematics 8(5):672

    Google Scholar 

  • Alcantud JCR, Mathew TJ (2017) Separable fuzzy soft sets and decision making with positive and negative attributes. Appl Soft Comput 59:586–595

    Google Scholar 

  • Alcantud JCR, Santos-García G (2017) A new criterion for soft set based decision-making problems under incomplete information. Int J Comput Intell Syst 10:394–404

    Google Scholar 

  • Alcantud JCR, Torra V (2018) Decomposition theorems and extension principles for hesitant fuzzy sets. Inf Fus 41:48–56

    Google Scholar 

  • Alcantud JCR, Cruz-Rambaud S, Torrecillas MJ (2017a) Valuation fuzzy soft sets: a flexible fuzzy soft set based decision making procedure for the valuation of assets. Symmetry 9:253

    MATH  Google Scholar 

  • Alcantud JCR, Torrecillas MJ, Muñoz (2017b) Intertemporal choice of fuzzy soft sets. Symmetry 9:253

    MATH  Google Scholar 

  • Alcantud JCR, Feng F, Yager RR (2020) An N-soft set approach to rough sets. IEEE Trans Fuzzy Syst 28(11):2996–3007

    Google Scholar 

  • Ali MI, Feng F, Liu XY, Min WK, Shabir M (2009) On some new operations in soft set theory. Comput Math Appl 57(9):1547–1553

    MathSciNet  MATH  Google Scholar 

  • Al-Qudah Y, Hassan N (2017) Operations on complex multi-fuzzy sets. J Intell Fuzzy Syst 33:1527–1540

    MATH  Google Scholar 

  • Al-Qudah Y, Hassan N (2018) Complex multi-fuzzy soft set: its entropy and similarity measure. IEEE Access 6:65002–65017

    Google Scholar 

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

    MathSciNet  MATH  Google Scholar 

  • Azam M, Bouguila N (2019) Bounded generalized Gaussian mixture model with ICA. Neural Process Lett 49:1299–1320

    Google Scholar 

  • Azam M, Bouguila N (2020) Multivariate bounded support Laplace mixture model. Soft Comput 24:13239–13268

    Google Scholar 

  • Çağman N, Çitak F, Enginoğlu S (2010) Fuzzy parameterized fuzzy soft set theory and its applications. Turk J Fuzzy Syst 1(1):21–35

    MATH  Google Scholar 

  • Çağman N, Çitak F, Enginoğlu S (2011) FP-soft set theory and its applications. Ann Fuzzy Math Inform 2(2):219–226

    MathSciNet  MATH  Google Scholar 

  • Chen Y, Liu J, Chen Z, Zhang Y (2020) Group decision-making method based on generalized vague N-soft sets. In: Chinese control and decision conference (CCDC), pp 4010–4015

  • Das S, Kar S (2013) Intuitionistic multi fuzzy soft set and its application in decision making. In: Maji P, Ghosh A, Murty MN, Ghosh K, Pal SK (eds) Pattern recognition and machine intelligence. PReMI 2013. Lecture notes in computer science, vol 8251. Springer, Berlin. https://doi.org/10.1007/978-3-642-45062-4_82

  • Dey A, Pal M (2015) Generalised multi-fuzzy soft set and its application in decision making. Pac Sci Rev A Nat Sci Eng 17(1):23–28

    Google Scholar 

  • Fatimah F, Alcantud JCR (2021) The multi-fuzzy N-soft set and its applications to decision-making. Neural Comput Appl. https://doi.org/10.1007/s00521-020-05647-3

    Article  Google Scholar 

  • Fatimah F, Rosadi D, Hakim RBF (2018a) Probabilistic soft sets and dual probabilistic soft sets in decision making with positive and negative parameters. J Phys Conf Ser 983(1):012112

    Google Scholar 

  • Fatimah F, Rosadi D, Hakim RBF, Alcantud JCR (2018b) N-soft sets and their decision-making algorithms. Soft Comput 22(12):3829–3842

    MATH  Google Scholar 

  • Fatimah F, Rosadi D, Hakim RBF, Alcantud JCR (2019) Probabilistic soft sets and dual probabilistic soft sets in decision-making. Neural Comput Appl 31(Suppl 1):397–407

    Google Scholar 

  • Fatimah F, Alcantud JCR (2018) Expanded dual hesitant fuzzy sets. In: International conference on intelligent systems (IS), pp 102–108. https://doi.org/10.1109/IS.2018.8710539

  • Kamacı H, Petchimuthu S (2020) Bipolar N-soft set theory with applications. Soft Comput 24:16727–16743

    MATH  Google Scholar 

  • Liu P, Zhang L (2017a) An extended multiple criteria decisionmaking method based on neutrosophic hesitant fuzzy information. J Intell Fuzzy Syst 32(6):4403–4413

    MATH  Google Scholar 

  • Liu P, Zhang L (2017b) Multiple criteria decision-making method based on neutrosophic hesitant fuzzy Heronian mean aggregation operators. J Intell Fuzzy Syst 32(1):303–319

    MATH  Google Scholar 

  • Liu X, Kim H, Feng F, Alcantud JCR (2018) Centroid transformations of intuitionistic fuzzy values based on aggregation operators. Mathematics 6(11):215

    MATH  Google Scholar 

  • Liu J, Chen Y, Chen Z, Zhang Y (2020) Multi-attribute decision making method based on neutrosophic vague N-soft sets. Symmetry 12:853

    Google Scholar 

  • Ma X, Liu Q, Zhang J (2017) A survey of decision-making methods based on certain hybrid soft set models. Artif Intell Rev 47(4):507–530

    Google Scholar 

  • Maji PK, Biswas R, Roy AR (2001a) Fuzzy soft sets. J Fuzzy Math 9(3):589–602

    MathSciNet  MATH  Google Scholar 

  • Maji PK, Biswas R, Roy AR (2001b) Intuitionistic fuzzy soft sets. J Fuzzy Math 9(3):677–692

    MathSciNet  MATH  Google Scholar 

  • Maji PK, Biswas R, Roy AR (2002) An application of soft sets in decision-making problem. Comput Math Appl 44(8–9):1077–1083

    MathSciNet  MATH  Google Scholar 

  • Maji PK, Biswas R, Roy AR (2003) Soft set theory. Comput Math Appl 45(4–5):555–562

    MathSciNet  MATH  Google Scholar 

  • Maji PK, Roy AR, Biswas R (2004) On intuitionistic fuzzy soft sets. J Fuzzy Math 12(3):669–683

    MathSciNet  MATH  Google Scholar 

  • Mohammed MA, Abdulkareem KH et al (2020) Benchmarking methodology for selection of optimal COVID-19 diagnostic model based on entropy and TOPSIS methods. IEEE Access 8:99115–99131

    Google Scholar 

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

    MathSciNet  MATH  Google Scholar 

  • Peng X, Dai J (2017) Hesitant fuzzy soft decision-making methods based on WASPAS, MABAC and COPRAS with combined weights. J Intell Fuzzy Syst 33(2):1313–1325

    MATH  Google Scholar 

  • Peng XD, Garg H (2018) Algorithms for interval-valued fuzzy soft sets in emergency decision-making based on WDBA and CODAS with new information measure. Comput Ind Eng 119:439–452

    Google Scholar 

  • Peng XD, Liu C (2017) Algorithms for neutrosophic soft decision making based on EDAS, new similarity measure and level soft set. J Intell Fuzzy Syst 32(1):955–968

    MATH  Google Scholar 

  • Peng XD, Yang Y (2017) Algorithms for interval-valued fuzzy soft sets in stochastic multi-criteria decision-making based on regret theory and prospect theory with combined weight. Appl Soft Comput 54:415–430

    Google Scholar 

  • Riaz M, Çagman N, Zareef I, Aslaam M (2019) N-soft topology and its applications to multi-criteria group decision making. J Intell Fuzzy Syst 36(6):6521–6536

    Google Scholar 

  • Riaz M, Naeem K, Zareef I, Afzal D (2020) Neutrosophic N-soft sets with TOPSIS method for multiple attribute decision making. Neutrosophic Sets Syst 32:1–23

    Google Scholar 

  • Roy AR, Maji PK (2007) A fuzzy soft set theoretic approach to decision making problems. J Comput Appl Math 203:412–418

    MATH  Google Scholar 

  • Sebastian S, Ramakrishnan TV (2011) Multi-fuzzy sets: an extension of fuzzy sets. Fuzzy Inf Eng 1:35–43

    MathSciNet  MATH  Google Scholar 

  • Shinoj TK, John SJ (2012) Intuitionistic fuzzy multisets and its application in medical diagnosis. World Acad Sci Eng Technol 61:1178–1181

    Google Scholar 

  • Terepeta M (2019) On separating axioms and similarity of soft topological spaces. Soft Comput 23(3):1049–1057

    MATH  Google Scholar 

  • Torra V (2010) Hesitant fuzzy sets. Int J Intell Syst 25(6):529–539

    MATH  Google Scholar 

  • Torra V, Narukawa Y (2009) On hesitant fuzzy sets and decisions. IEEE Int Conf Fuzzy Syst 1–3:1378–1382

    Google Scholar 

  • Xia MM, Xu ZS (2011) Hesitant fuzzy information aggregation in decision-making. Int J Approx Reason 52:395–407

    MathSciNet  MATH  Google Scholar 

  • Yang XB, Lin TY, Yang JY, Li Y, Yu D (2009) Combination of interval-valued fuzzy set and soft set. Comput Math Appl 58(3):521–527

    MathSciNet  MATH  Google Scholar 

  • Yang Y, Tan X, Meng C (2013) The multi-fuzzy soft set and its application in decision making. Appl Math Model 37:4915–4923

    MathSciNet  MATH  Google Scholar 

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

    MATH  Google Scholar 

  • Zhan J, Alcantud JCR (2019) A survey of parameter reduction of soft sets and corresponding algorithms. Artif Intell Rev 52(3):1839–1872

    Google Scholar 

  • Zhu B, Xu ZS, Xu JP (2014) Deriving a ranking from hesitant fuzzy preference relations under group decision-making. IEEE Trans Cybern 44(8):1328–2119

    Google Scholar 

Download references

Acknowledgements

The authors would like to express their gratitude to the editors and anonymous referees for their informative, helpful remarks and suggestions to improve this paper as well as the important guiding significance to our researches.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ajoy Kanti Das.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Das, A.K., Granados, C. IFP-intuitionistic multi fuzzy N-soft set and its induced IFP-hesitant N-soft set in decision-making. J Ambient Intell Human Comput 14, 10143–10152 (2023). https://doi.org/10.1007/s12652-021-03677-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12652-021-03677-w

Keywords

Navigation