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Intertemporal Hesitant Fuzzy Soft Sets: Application to Group Decision Making

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Abstract

A novel hybrid soft set model called intertemporal hesitant fuzzy soft set is proposed, and then, it is showed how it can deal with group decision making problems. This model can be used to incorporate hesitant information that varies across time, when the alternatives are described by their degree of agreement with various characteristics. According to the period of time (whether it is indefinitely long or with a known termination date), the proposed model is, respectively, called long-term and short-term intertemporal hesitant fuzzy soft set. Corresponding group decision making approaches are provided, where the application of Quasi-Hyperbolic discounting permits to deal with the time-inconsistent experts’ preferences. Both the effect of scores of hesitant fuzzy elements and the effect of uncertainty contained in hesitant information are considered in the proposed decision approaches.

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References

  1. Akram, M., Adeel, A., Alcantud, J.C.R.: Fuzzy \(N\)-soft sets: a novel model with applications. J. Intell. Fuzzy Syst. 35(11), 1–15 (2018)

    Google Scholar 

  2. Akram, M., Adeel, A., Alcantud, J.C.R.: Group decision-making methods based on hesitant \(N\)-soft sets. Expert Syst. Appl. 115, 95–105 (2019)

    Google Scholar 

  3. Alcantud, J.C.R.: A novel algorithm for fuzzy soft set based decision making from multiobserver input parameter data set. Inf. Fusion 29, 142–148 (2016)

    Google Scholar 

  4. Alcantud, J.C.R.: Some formal relationships among soft sets, fuzzy sets, and their extensions. Int. J. Approx. Reason. 68, 45–53 (2016)

    MathSciNet  MATH  Google Scholar 

  5. Alcantud, J.C.R., Giarlotta, A.: Necessary and possible hesitant fuzzy sets: a novel model for group decision making. Inf. Fusion 46, 63–76 (2019)

    Google Scholar 

  6. Alcantud, J.C.R., Mathew, T.J.: Separable fuzzy soft sets and decision making with positive and negative attributes. Appl. Soft. Comput. 59, 586–595 (2017)

    Google Scholar 

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

    Google Scholar 

  8. Alcantud, J.C.R., Torra, V.: Decomposition theorems and extension principles for hesitant fuzzy sets. Inf. Fusion 41, 48–56 (2018)

    Google Scholar 

  9. Alcantud, J.C.R., Muñoz Torrecillas, M.A.J.: Intertemporal choice of fuzzy soft sets. Symmetry Basel 10(9), 371 (2018). https://doi.org/10.3390/sym10090371

    Article  MATH  Google Scholar 

  10. Aliahmadipour, L., Torra, V., Eslami, E., Eftekhari, M.: A definition for hesitant fuzzy partitions. Int. J. Comput. Intell. Syst. 9(3), 497–505 (2016)

    Google Scholar 

  11. Berns, G.S., Laibson, D., Loewenstein, G.: Intertemporal choice-toward an integrative framework. Trends Cogn. Sci. 11(11), 482–488 (2007)

    Google Scholar 

  12. Bustince, H., Barrenechea, E., Pagola, M., Fernández, J., Xu, Z., Bedregal, B., Montero, J., Hagras, H., Herrera, F., Baets, B.D.: A historical account of types of fuzzy sets and their relationships. IEEE Trans. Fuzzy Syst. 24(1), 179–194 (2016)

    Google Scholar 

  13. Diamond, P., Köszegi, B.: Quasi-hyperbolic discounting and retirement. J. Public Econ. 87(9), 1839–1872 (2003)

    Google Scholar 

  14. Farhadinia, B.: Multicriteria decision making method based on the higher order hesitant fuzzy soft set. Int. Scholarly Res. Not. 2014, 1–11 (2014)

    MATH  Google Scholar 

  15. Farhadinia, B.: A series of score functions for hesitant fuzzy sets. Inf. Sci. 277(2), 102–110 (2014)

    MathSciNet  MATH  Google Scholar 

  16. Fatimah, F., Rosadi, D., Hakim, R.B.F., Alcantud, J.C.R.: \(N\)-soft sets and their decision making algorithms. Soft Comput. 22(12), 3829–3842 (2018)

    MATH  Google Scholar 

  17. Feng, F., Jun, Y.B., Liu, X., Li, L.: An adjustable approach to fuzzy soft set based decision making. J. Comput. Appl. Math. 234(1), 10–20 (2010)

    MathSciNet  MATH  Google Scholar 

  18. Fisher, I.: The Theory of Interest: As Determined by Impatience to Spend Income and Opportunity to Invest. Macmillan, New York (1930)

    MATH  Google Scholar 

  19. Kong, Z., Gao, L., Wang, L.: Comment on “A fuzzy soft set theoretic approach to decision making problems”. J. Comput. Appl. Math. 223(2), 540–542 (2009)

    MATH  Google Scholar 

  20. Krishankumar, R., Subrajaa, L.S., Ravichandran, K.S., Kar, S., Saeid, A.B.: A framework for multi-attribute group decision-making using double hierarchy hesitant fuzzy linguistic term set. Int. J. Fuzzy Syst. (2019). https://doi.org/10.1007/s40815-019-00618-w

    Article  MathSciNet  Google Scholar 

  21. Laibson, D.: Golden eggs and hyperbolic discounting. Quart. J. Econ. 112(2), 443–477 (1997)

    MATH  Google Scholar 

  22. Liu, Y., Luo, J., Wang, B., Qin, K.: A theoretical development on the entropy of interval-valued intuitionistic fuzzy soft sets based on the distance measure. Int. J. Comput. Intell. Syst. 10(1), 569–592 (2017)

    Google Scholar 

  23. Liu, Y., Qin, K., Martínez, L.: Improving decision making approaches based on fuzzy soft sets and rough soft sets. Appl. Soft. Comput. 65, 320–332 (2018)

    Google Scholar 

  24. Liu, Y., Qin, K., Rao, C., Mahamadu, M.A.: Object-parameter approaches to predicting unknown data in an incomplete fuzzy soft set. Int. J. Appl. Math. Comput. Sci. 27(1), 157–167 (2017)

    MathSciNet  MATH  Google Scholar 

  25. Liu, Y., Zhao, H., Xu, Z.: An orthogonal clustering method under hesitant fuzzy environment. Int. J. Comput. Intell. Syst. 10(1), 663–676 (2017)

    Google Scholar 

  26. Loewenstein, G., Prelec, D.: Anomalies in intertemporal choice: evidence and an interpretation. Quart. J. Econ. 107(2), 573–597 (1992)

    Google Scholar 

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

    MathSciNet  MATH  Google Scholar 

  28. Phelps, E., Pollak, R.: On second-best national saving and game-equilibrium growth. The Rev. Econ. Stud. 35(2), 185–199 (1968)

    Google Scholar 

  29. Roy, A.R., Maji, P.: A fuzzy soft set theoretic approach to decision making problems. J. Comput. Appl. Math. 203(2), 412–418 (2007)

    MATH  Google Scholar 

  30. Samuelson, P.A.: A note on measurement of utility. Rev. Econ. Stud. 4(2), 155–161 (1937)

    MathSciNet  Google Scholar 

  31. Shaheen, T., Mian, B., Shabir, M., Feng, F.: A novel approach to decision analysis using dominance-based soft rough sets. Int. J. Fuzzy Syst. 21(3), 954–962 (2019)

    MathSciNet  Google Scholar 

  32. Streich, P., Levy, J.S.: Time horizons, discounting, and intertemporal choice. J. Confl. Resolut. 51(2), 199–226 (2007)

    Google Scholar 

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

    MATH  Google Scholar 

  34. Wang, F., Li, X., Chen, X.: Hesitant fuzzy soft set and its applications in multicriteria decision making. J. Appl. Math. 7(3), 1–10 (2014)

    MATH  Google Scholar 

  35. Wang, H., Xu, Z.: Multi-groups decision making using intuitionistic-valued hesitant fuzzy information. Int. J. Comput. Intell. Syst. 9(3), 468–482 (2016)

    Google Scholar 

  36. Wang, L., Qin, K.: Robustness of general triple i method for fuzzy soft sets. Int. J. Comput. Intell. Syst. 11, 1111–1122 (2018)

    Google Scholar 

  37. Xu, Z., Xia, M.: Hesitant fuzzy entropy and cross-entropy and their use in multiattribute decision-making. In: IEEE global telecommunications conference on IEEE GLOBECOM 2007, pp. 700–704 (2007)

  38. Xu, Z., Xia, M.: Hesitant fuzzy entropy and cross-entropy and their use in multiattribute decision-making. Int. J. Intell. Syst. 27(9), 799–822 (2012)

    Google Scholar 

  39. Yang, W., Pang, Y., Shi, J.: Linguistic hesitant intuitionistic fuzzy cross-entropy measures. Int. J. Comput. Intell. Syst. 10(1), 120–139 (2017)

    Google Scholar 

  40. Yu, W., Zhang, Z., Zhong, Q., Sun, L.: Extended TODIM for multi-criteria group decision making based on unbalanced hesitant fuzzy linguistic term sets. Comput. Ind. Eng. 114, 316–328 (2017)

    Google Scholar 

  41. Zhan, J., Ali, M.I., Mehmood, N.: On a novel uncertain soft set model: Z-soft fuzzy rough set model and corresponding decision making methods. Appl. Soft. Comput. 56, 446–457 (2017)

    Google Scholar 

  42. Zhan, J., Liu, Q., Herawan, T.: A novel soft rough set: soft rough hemirings and corresponding multicriteria group decision making. Appl. Soft. Comput. 54, 393–402 (2017)

    Google Scholar 

  43. Zhan, J., Zhu, K.: A novel soft rough fuzzy set: Z-soft rough fuzzy ideals of hemirings and corresponding decision making. Soft Comput. 21(8), 1923–1936 (2017)

    MATH  Google Scholar 

  44. Zhang, Z., Guo, C., Martínez, L.: Managing multigranular linguistic distribution assessments in large-scale multiattribute group decision making. IEEE Trans. Syst. Man Cybern. -Syst. 47(11), 3063–3076 (2017)

    Google Scholar 

  45. Zhang, Z., Kou, X., Dong, Q.: Additive consistency analysis and improvement for hesitant fuzzy preference relations. Expert Syst. Appl. 98, 118–128 (2018)

    Google Scholar 

  46. Zhang, Z., Kou, X., Yu, W., Guo, C.: On priority weights and consistency for incomplete hesitant fuzzy preference relations. Knowledge Based Syst 143, 115–126 (2018)

    Google Scholar 

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Acknowledgements

This work is partially supported by the Spanish National Research Project TIN2015-66524-P and PGC2018-099402-B-I00, Spanish Ministry of Economy and Competitiveness, Postdoctoral fellow Ramón y Cajal (RYC-2017-21978), and the National Natural Science Foundation of China (Grant Nos. 61473239, 61603307).

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Authors and Affiliations

  1. Business School, University of Shanghai for Science and Technology, Shanghai, 200093, China

    Yaya Liu

  2. Facultad de Economía y Empresa, BORDA Research Unit and Multidisciplinary Institute of Enterprise (IME), University of Salamanca, Salamanca, 37007, Spain

    José Carlos R. Alcantud

  3. Department of Computer Science, University of Jaén, Jaén, 23071, Spain

    Rosa M. Rodríguez & Luis Martínez

  4. College of Mathematics, Southwest Jiaotong University, Chengdu, 610031, Sichuan, China

    Keyun Qin

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  1. Yaya Liu
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  2. José Carlos R. Alcantud
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  3. Rosa M. Rodríguez
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  4. Keyun Qin
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  5. Luis Martínez
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Correspondence to Yaya Liu.

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Liu, Y., Alcantud, J.C.R., Rodríguez, R.M. et al. Intertemporal Hesitant Fuzzy Soft Sets: Application to Group Decision Making. Int. J. Fuzzy Syst. 22, 619–635 (2020). https://doi.org/10.1007/s40815-020-00798-w

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