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An Attitudinal Nonlinear Integral and Applications in Decision Making

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Abstract

In the field of information fusion and decision making, integral is very common and important for aggregating a large variety of information. The integral to be used is usually nonlinear due to the nonadditive measure determined by the real world. In this study, we put forward a new nonlinear integral, which is first expressed as an interval, containing the infimum and supremum of the integrand on the nonadditive measure. Furthermore, an attitudinal nonlinear integral is defined by introducing the subjective attitude of the decision maker based on the integral interval obtained. A multi-criteria decision-making (MCDM) method considering the interaction between attribute features is developed based on the proposed attitudinal nonlinear integral and a case study is provided to demonstrate the usefulness of the decision-making method. Inspired by the golden rule representation, we define the generalized golden rule representative value of the interval integral and use it to solve the problem in the case study to illustrate its usefulness.

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References

  1. Han, Y., Deng, Y., Cao, Z., Lin, C.-T.: An interval-valued pythagorean prioritized operator based game theoretical framework with its applications in multicriteria group decision making. Neural Comput. Appl. (2019). https://doi.org/10.1007/s00521-019-04014-1

    Article  Google Scholar 

  2. Zhang, H., Deng, Y.: Weighted belief function of sensor data fusion in engine fault diagnosis. Soft Comput. 24(3), 2329–2339 (2020)

    Article  MathSciNet  Google Scholar 

  3. Fei, L., Deng, Y.: Multi-criteria decision making in pythagorean fuzzy environment. App. Intell. 50(2), 537–561 (2020)

    Article  Google Scholar 

  4. Liu, P., Cheng, S.: An extension of aras methodology for multi-criteria group decision-making problems within probability multi-valued neutrosophic sets. Int. J. Fuzzy Syst. 21(8), 2472–2489 (2019)

    Article  MathSciNet  Google Scholar 

  5. Pan, L., Deng, Y.: An association coefficient of a belief function and its application in a target recognition system. Int. J. Intell. Syst. 35(1), 85–104 (2020)

    Article  Google Scholar 

  6. Liu, P., Wang, P.: Multiple attribute group decision making method based on intuitionistic fuzzy Einstein interactive operations. Int. J. Fuzzy Syst. (2020). https://doi.org/10.1007/s40815-020-00809-w

    Article  Google Scholar 

  7. Fei, L., Feng, Y., Liu, L.: Evidence combination using owa-based soft likelihood functions. Int. J. Intell. Syst. 34(9), 2269–2290 (2019)

    Article  Google Scholar 

  8. Xiao, F.: EFMCDM: Evidential fuzzy multicriteria decision making based on belief entropy. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2936368

    Article  Google Scholar 

  9. Li, Y., Deng, Y.: Tdbf: Two-dimensional belief function. Int. J. Intell. Syst. 34(8), 1968–1982 (2019)

    Article  Google Scholar 

  10. Jiang, W., Huang, C., Deng, X.: A new probability transformation method based on a correlation coefficient of belief functions. Int. J. Intell. Syst. 34(6), 1337–1347 (2019)

    Article  Google Scholar 

  11. Fei, L., Lu, J., Feng, Y.: An extended best-worst multi-criteria decision-making method by belief functions and its applications in hospital service evaluation. Comput. Industr. Eng. 142, 106355 (2020). https://doi.org/10.1016/j.cie.2020.106355

    Article  Google Scholar 

  12. Fei, L., Wang, H., Chen, L., Deng, Y.: A new vector valued similarity measure for intuitionistic fuzzy sets based on owa operators. Iran. J. Fuzzy Syst. 16(3), 113–126 (2019)

    MathSciNet  MATH  Google Scholar 

  13. Xiao, F.: A distance measure for intuitionistic fuzzy sets and its application to pattern classification problems. IEEE Trans. Syst. Man Cybern. (2019). https://doi.org/10.1109/TSMC.2019.2958635

    Article  Google Scholar 

  14. Zeng, S., Chen, S.-M., Kuo, L.-W.: Multiattribute decision making based on novel score function of intuitionistic fuzzy values and modified Vikor method. Inform. Sci. 488, 76–92 (2019)

    Article  Google Scholar 

  15. Song, Y., Fu, Q., Wang, Y.-F., Wang, X.: Divergence-based cross entropy and uncertainty measures of Atanassov’s intuitionistic fuzzy sets with their application in decision making. Appl. Soft Comput. (2019). https://doi.org/10.1016/j.asoc.2019.105703

    Article  Google Scholar 

  16. Fei, L., Feng, Y., Liu, L.: On pythagorean fuzzy decision making using soft likelihood functions. Int. J. Intell. Syst. 34(12), 3317–3335 (2019)

    Article  Google Scholar 

  17. Xiao, F., Zhang, Z., Abawajy, J.: Workflow scheduling in distributed systems under fuzzy environment. J. Intell. Fuzzy Syst. 37(4), 5323–5333 (2019)

    Article  Google Scholar 

  18. Fei, L.: D-anp: a multiple criteria decision making method for supplier selection. Appl. Intell. (2020). https://doi.org/10.1007/s10489-020-01639-x

    Article  Google Scholar 

  19. Deng, X., Jiang, W.: D number theory based game-theoretic framework in adversarial decision making under a fuzzy environment. Int. J. Approx. Reason. 106, 194–213 (2019)

    Article  MathSciNet  Google Scholar 

  20. Han, Y., Deng, Y.: A novel matrix game with payoffs of maxitive belief structure. Int. J. Intell. Syst. 34(4), 690–706 (2019)

    Article  Google Scholar 

  21. Deng, X., Jiang, W.: A total uncertainty measure for d numbers based on belief intervals. Int. J. Intell. Syst. 34(12), 3302–3316 (2019)

    Article  Google Scholar 

  22. Jiang, W., Cao, Y., Deng, X.: A Novel Z-network Model Based on Bayesian Network and Z-number. IEEE Trans. Fuzzy Syst. (2019). https://doi.org/10.1109/TFUZZ.2019.2918999

    Article  Google Scholar 

  23. Li, D., Deng, Y.: A new correlation coefficient based on generalized information quality. IEEE Access 7, 175411–175419 (2019)

    Article  Google Scholar 

  24. Fei, L., Xia, J., Feng, Y., Liu, L.: An electre-based multiple criteria decision making method for supplier selection using Dempster–Shafer theory. IEEE Access 7, 84701–84716 (2019)

    Article  Google Scholar 

  25. Felix, R.: Relationships between goals in multiple attribute decision making. Fuzzy Sets Syst. 67(1), 47–52 (1994)

    Article  MathSciNet  Google Scholar 

  26. Grabisch, M., et al.: The application of fuzzy integrals in multicriteria decision making. Eur. J. Oper. Res. 89(3), 445–456 (1996)

    Article  Google Scholar 

  27. Liao, H., Gou, X., Xu, Z., Zeng, X.-J., Herrera, F.: Hesitancy degree-based correlation measures for hesitant fuzzy linguistic term sets and their applications in multiple criteria decision making. Inform. Sci. 508, 275–292 (2020)

    Article  MathSciNet  Google Scholar 

  28. Fang, R., Liao, H., Yang, J.-B., Xu, D.-L.: Generalised probabilistic linguistic evidential reasoning approach for multi-criteria decision-making under uncertainty. J. Oper. Res. Soc. (2019). https://doi.org/10.1080/01605682.2019.1654415

    Article  Google Scholar 

  29. G. Choquet, Theory of capacities. In: Annales de l’institut Fourier. (1954) Vol. 5, pp. 131–295

  30. M. Sugeno, Theory of fuzzy integrals and its applications, Doct. Thesis, Tokyo Institute of technology

  31. Corrente, S., Greco, S., Ishizaka, A.: Combining analytical hierarchy process and Choquet integral within non-additive robust ordinal regression. Omega 61, 2–18 (2016)

    Article  Google Scholar 

  32. Büyüközkan, G., Göçer, F.: Smart medical device selection based on intuitionistic fuzzy Choquet integral. Soft Comput. 23(20), 10085–10103 (2019)

    Article  Google Scholar 

  33. Zhang, D., Bao, X., Wu, C.: An extended todim method based on novel score function and accuracy function under intuitionistic fuzzy environment. Int. J. Uncert. Fuzz. Knowl. Based Syst. 27(06), 905–930 (2019)

    Article  MathSciNet  Google Scholar 

  34. Yager, R.R.: Multi-criteria decision making with interval criteria satisfactions using the golden rule representative value. IEEE Trans. Fuzzy Syst. 26(2), 1023–1031 (2017)

    Article  Google Scholar 

  35. Li, X., Zhang, X.: Sugeno integral of set-valued functions with respect to multi-submeasures and its application in madm. Int. J. Fuzzy Syst. 20(8), 2534–2544 (2018)

    Article  MathSciNet  Google Scholar 

  36. Wang, Z., Leung, K.-S., Wong, M.-L., Fang, J.: A new type of nonlinear integrals and the computational algorithm. Fuzzy Sets Syst. 112(2), 223–231 (2000)

    Article  MathSciNet  Google Scholar 

  37. Zeng, S., Mu, Z.: Method based on zhenyuan integral for intuitionistic fuzzy multiple attribute decision making. Contr. Decis. 33(3), 542–548 (2018)

    MATH  Google Scholar 

  38. Mu, Z., Zeng, S.: Some novel intuitionistic fuzzy information fusion methods in decision making with interaction among attributes. Soft Comput. 23(20), 10439–10448 (2019)

    Article  Google Scholar 

  39. Z. Liu, F. Xiao, C.-T. Lin, B. H. Kang, Z. Cao, A generalized golden rule representative value for multiple-criteria decision analysis. IEEE Trans. Syst. Man Cybern

  40. Li, P., Fei, L.: On combination rule in dempster-shafer theory using owa-based soft likelihood functions and its applications in environmental impact assessment. Int. J. Intell. Syst. 34(12), 3168–3189 (2019)

    Article  Google Scholar 

  41. Y. Song, X. Wang, W. Quan, W. Huang, A new approach to construct similarity measure for intuitionistic fuzzy sets. Soft Comput. (2019) 23 (6, SI): 1985–1998

  42. Xiao, F.: A new divergence measure for belief functions in D-S evidence theory for multisensor data fusion. Inform. Sci. 514, 462–483 (2020)

    Article  MathSciNet  Google Scholar 

  43. Fei, L.: On interval-valued fuzzy decision-making using soft likelihood functions. Int. J. Intell. Syst. 34(7), 1631–1652 (2019)

    Article  Google Scholar 

  44. Liu, Z., Xiao, F.: An interval-valued exceedance method in mcdm with uncertain satisfactions. Int. J. Intell. Syst. 34(10), 2676–2691 (2019)

    Article  Google Scholar 

  45. Jiang, W., Wei, B., Liu, X., Li, X., Zheng, H.: Intuitionistic fuzzy power aggregation operator based on entropy and its application in decision making. Int. J. Intell. Syst. 33(1), 49–67 (2018)

    Article  Google Scholar 

  46. Fei, L., Deng, Y., Hu, Y.: Ds-vikor: A new multi-criteria decision-making method for supplier selection. Int. J. Fuzzy Syst. 21(1), 157–175 (2019)

    Article  MathSciNet  Google Scholar 

  47. Xiao, F.: Generalization of Dempster-Shafer theory: a complex mass function. Appl. Intell. (2019). https://doi.org/10.1007/s10489-019-01617-y

    Article  Google Scholar 

  48. Z. Cao, W. Ding, Y.-K. Wang, F. K. Hussain, A. Al-Jumaily, C.-T. Lin, Effects of repetitive ssveps on eeg complexity using multiscale inherent fuzzy entropy, Neurocomputing

  49. Yager, R.R.: Golden rule and other representative values for intuitionistic membership grades. IEEE Trans. Fuzzy Syst. 23(6), 2260–2269 (2015)

    Article  Google Scholar 

  50. Aggarwal, M.: Attitudinal Choquet integrals and applications in decision making. Int. J. Intell. Syst. 33(4), 879–898 (2018)

    Article  Google Scholar 

  51. Gao, X., Liu, F., Pan, L., Deng, Y., Tsai, S.-B.: Uncertainty measure based on tsallis entropy in evidence theory. Int. J. Intell. Syst. 34(11), 3105–3120 (2019)

    Article  Google Scholar 

  52. Liao, H., Zhang, C., Luo, L., Xu, Z., Yang, J.-B., Xu, D.-L.: Distance-based intuitionistic multiplicative multiple criteria decision-making methods for healthcare management in West China hospital. Expert Syst. 1, e12479 (2019)

    Google Scholar 

  53. Aggarwal, M.: Generalized attitudinal Choquet integral. Int. J. Intell. Syst. 34(5), 733–753 (2019)

    Article  Google Scholar 

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Acknowledgements

We appreciate the encouragement of editors and anonymous reviewers. This research was funded by the grants from the National Natural Science Foundation of China (#71472053, #71429001, #91646105).

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Correspondence to Liguo Fei.

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Fei, L., Feng, Y. An Attitudinal Nonlinear Integral and Applications in Decision Making. Int. J. Fuzzy Syst. 23, 564–572 (2021). https://doi.org/10.1007/s40815-020-00862-5

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  • DOI: https://doi.org/10.1007/s40815-020-00862-5

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