Abstract
Hesitant fuzzy linguistic term sets (HFLTSs) provide a linguistic and computational basis to increase the flexibility and richness of linguistic elicitation based on the fuzzy linguistic approach. Based on the traditional Hamming distance, Euclidean distance and generalized distance, some new class of distance measures for hesitant fuzzy linguistic numbers which include the hesitance degree of hesitant fuzzy element are provided and some linguistic scale functions are applied. We also define the continuous distance measure between two collections of HFLTSs. Furthermore, the proposed distance measures based on TOPSIS method for hesitant fuzzy linguistic multiple criteria decision making are developed, which calculate the distances between the alternatives and the positive ideal solution, the negative ideal solution, respectively. Then, the relative closeness degree to the ideal solution is calculated to rank all the alternatives. The main characteristics of the proposed distance measures are that it not only considers the hesitance of the hesitant fuzzy elements but also deals with linguistic transformation problem under different semantic situations, which efficiently avoid information loss and distortion. Finally, an example is provided to illustrate the feasibility and effectiveness of the developed method, which are then compared to the existing methods.
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Zadeh, L.A.: Fuzzy sets. Inf. Control 8(3), 338–353 (1965)
Yager, R.R.: Multiple objective decision-making using fuzzy sets. Int. J. Man Mach. Stud. 9(4), 375–382 (1977)
Khatibi, V., Montazer, G.A.: Intuitionistic fuzzy set vs. fuzzy set application in medical pattern recognition. Artif. Intell. Med. 47(1), 43–52 (2009)
Cateni, S., Vannucci, M., Colla, V.: Industrial multiple criteria decision making problems handled by means of fuzzy inference-based decision support systems. In: International Conference on Intelligent Systems, Modelling and Simulation. pp. 12–17. IEEE Computer Society (2013)
Torra, V., Narukawa, Y.: On hesitant fuzzy sets and decision. In: IEEE International Conference on Fuzzy Systems, 2009. pp. 1378–1382. Fuzz-Ieee. IEEE (2009)
Torra, V.: Hesitant fuzzy sets. Int. J. Intell. Syst. 25(6), 529–539 (2010)
Xia, M., Xu, Z.: Hesitant fuzzy information aggregation in decision making. Int. J. Approx. Reason. 52(3), 395–407 (2011)
Farhadinia, B.: A series of score functions for hesitant fuzzy sets. Inf. Sci. 277(2), 102–110 (2014)
Rodrguez, R.M., Martnez, L., Torra, V., et al.: Hesitant fuzzy sets: state of the art and future directions. Int. J. Intell. Syst. 29(6), 495–524 (2014)
Herrera, F., Verdegay, J.L.: Linguistic assessments in group decision. In: Proceedings of First European Congress on Fuzzy and Intelligent Technologies, Aachen. pp. 941–948 (1993)
Herrera, F., Herrera-Viedma, E., Verdegay, J.L.: A model of consensus in group decision making under linguistic assessment. Fuzzy Sets Syst. 78(1), 73–87 (1996)
Herrera, F., Herrera-Viedma, E., Verdegay, J.L.: Direct approach processes in group decision making using linguistic OWA operators. Fuzzy Sets Syst. 79(2), 175–190 (1994)
Xu, Z.: An approach based on the uncertain LOWG and induced uncertain LOWG operators to group decision making with uncertain multiplicative linguistic preference relations. Decis. Support Syst. 41(2), 488–499 (2006)
Xu, Z.: Uncertain Multiple Attribute Decision Making : Methods and Applications. Tsinghua University, Beijing (2004)
Li, D.F., Chen, G.H., Huang, Z.G.: Linear programming method for multiattribute group decision making using IF sets. Inf. Sci. 180(9), 1591–1609 (2010)
Liu, P.: Some geometric aggregation operators based on interval intuitionistic uncertain linguistic variables and their application to group decision making. Appl. Math. Model. 37(4), 2430–2444 (2013)
Liu, P., Jin, F.: Methods for aggregating intuitionistic uncertain linguistic variables and their application to group decision making. Inf. Sci. Int. J. 205(1), 58–71 (2012)
Wang, J.Q., Peng, L., Zhang, H.Y., et al.: Method of multi-criteria group decision-making based on cloud aggregation operators with linguistic information. Inf. Sci. 274(274), 177–191 (2014)
Wang, X.F., Wang, J.Q., Yang, W.E.: Multi-criteria group decision making method based on intuitionistic linguistic aggregation operators. J. Intell. Fuzzy Syst. 26(3), 115–125 (2014)
Xian, S., Sun, W., Xu, S., et al.: Fuzzy linguistic induced OWA Minkowski distance operator and its application in group decision making. Pattern Anal. Appl. 19(2), 325–335 (2016)
Xian, S., Zhang, J., Xue, W.: Fuzzy linguistic induced generalized OWA operator and its application in fuzzy linguistic decision making. Int. J. Intell. Syst. 31(8), 749–762 (2016)
Rodriguez, R.M., MartíNez, L., Herrera, F.: Hesitant fuzzy linguistic term sets for decision making. IEEE Trans. Fuzzy Syst. 20(1), 109–119 (2012)
Chaudhuri, B.B., Rosenfeld, A.: A modified Hausdorff distance between fuzzy sets. Inf. Sci. Int. J. 118(1–4), 159–171 (1999)
Diamond, P., Kloeden, P.: Metric Spaces of Fuzzy Sets: Theory and Applications. WORLD SCIENTIFIC, Singapore (1994)
Palazoglu, A.: Multistage fuzzy control A model-based approach to fuzzy control and decision making: Janusz Kacprzyk. Wiley. New York (1997). J. Process Control 8(5), 517-517(1) (1998)
Liao, H., Xu, Z.: Approaches to manage hesitant fuzzy linguistic information based on the cosine distance and similarity measures for HFLTSs and their application in qualitative decision making. Expert Syst. Appl. 42(12), 5328–5336 (2015)
Meng, F., Chen, X.: A hesitant fuzzy linguistic multi-granularity decision making model based on distance measures. J. Intell. Fuzzy Syst. 28(4), 1519–1531 (2015)
Tong, X., Yu, L.: MADM based on distance and correlation coefficient measures with decision-maker preferences under a hesitant fuzzy environment. Soft Comput. 20(11), 1–13 (2016)
Szmidt, E., Kacprzyk, J.: Distances between intuitionistic fuzzy sets. Fuzzy Sets Syst. 114(3), 505–518 (2000)
Xu, Z., Xia, M.: Distance and similarity measures for hesitant fuzzy sets. Inf. Sci. 181(11), 2128–2138 (2011)
Li, D., Zeng, W., Li, J.: New distance and similarity measures on hesitant fuzzy sets and their applications in multiple criteria decision making. Eng. Appl. Artif. Intell. 40, 11–16 (2015)
Xu, Y., Wang, H.: Distance measure for linguistic decision making. Syst. Eng. Proc. 1(12), 450–456 (2011)
Wang, J.Q., Wu, J.T., Wang, J., et al.: Multi-criteria decision-making methods based on the Hausdorff distance of hesitant fuzzy linguistic numbers. Soft Comput. 20(4), 1621–1633 (2016)
Peng, D.H., Wang, T.D., Gao, C.Y., et al.: Enhancing relative ratio method for MCDM via attitudinal distance measures of interval-valued hesitant fuzzy sets. Int. J. Mach. Learn. Cybern. 8(4), 1347–1368 (2017)
Yu, D.J., Wu, Y.Y., Zhou, W.: Generalized hesitant fuzzy Bonferroni mean and its application in multi-criteria group decision making. J. Inf. Comput. Sci. 9(2), 267–274 (2012)
Xu, Z.: Linguistic Decision Making: Theory and Methods. Springer, Berlin (2013). (Incorporated)
Xu, Z.: Eowa and EOWG operators for aggregating linguistic labels based on linguistic preference relations. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 12(6), 791–810 (2004)
Acknowledgements
This research is fully supported by a grant by National Natural Science foundation of Hunan (2017JJ2096), by National Natural Science Foundation of China (11501191), by National Social Science Foundation of China (15BTJ028), by the Key International Collaboration Project of the National Nature Science Foundation of China (No. 71210003, Research on Electronic Business Based on the Users Behavior) by Major projects of the National Social Science Foundation of China (17ZDA046).
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Liu, D., Chen, X. & Peng, D. Distance Measures for Hesitant Fuzzy Linguistic Sets and Their Applications in Multiple Criteria Decision Making. Int. J. Fuzzy Syst. 20, 2111–2121 (2018). https://doi.org/10.1007/s40815-018-0460-0
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DOI: https://doi.org/10.1007/s40815-018-0460-0