Abstract
In this paper, a hesitant fuzzy power Maclaurin symmetric mean operator and a hesitant fuzzy weighted power Maclaurin symmetric mean operator are presented. The properties of these operators are explored and proved, and their special cases are discussed. Based on the presented operators, a new method is proposed to solve the multiple criteria decision making problems with hesitant fuzzy numbers. A numerical example is introduced to elucidate the application of the method. The advantages of the method are demonstrated via comparisons with some of the existing methods under a set of numerical examples. The demonstration results show that the proposed method has the capabilities to reduce the influence of biased evaluation values and consider the interrelationships between criteria, and more importantly it is free of the limitations of conventional operational laws of hesitant fuzzy numbers and appliable for the multiple criteria decision making problems where criterion weights are in the form of hesitant fuzzy numbers.
Similar content being viewed by others
References
Atanassov K (1986) Intuitionistic fuzzy sets. Fuzzy Sets Syst 20(1):87–96. https://doi.org/10.1016/S0165-0114(86)80034-3
Chen N, Xu Z (2015) Hesitant fuzzy ELECTRE II approach: a new way to handle multi-criteria decision making problems. Inf Ences 292:175–197. https://doi.org/10.1016/j.ins.2014.08.054
Chen N, Xu Z, Xia M (2013a) Interval-valued hesitant preference relations and their applications to group decision making. Knowl Based Syst 37:528–540. https://doi.org/10.1016/j.knosys.2012.09.009
Chen N, Xu Z, Xia M (2013b) Correlation coefficients of hesitant fuzzy sets and their applications to clustering analysis. Appl Math Model 37(4):2197–2211. https://doi.org/10.1002/int.22239
Chen C, Huang S, Hung W (2018) Linguistic VIKOR method for project evaluation of ambient intelligence product. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-018-0889-x
Dempster AP (1967) Upper and lower probabilities induced by a multi-valued mapping. Ann Stat 38(2):325–339. https://doi.org/10.1214/aoms/1177698950
Dymova L, Sevastjanov P (2010) An interpretation of intuitionistic fuzzy sets in terms of evidence theory: decision making aspect. Knowl Based Syst 23(8):772–782. https://doi.org/10.1016/j.knosys.2010.04.014
Dymova L, Sevastjanov P (2012) The operations on intuitionistic fuzzy values in the framework of Dempster–Shafer theory. Knowl Based Syst 35:132–143. https://doi.org/10.1016/j.knosys.2012.04.026
Dymova L, Sevastjanov P (2016) The operations on interval-valued intuitionistic fuzzy values in the framework of Dempster–Shafer theory. Inf Sci 360:256–272. https://doi.org/10.1016/j.ins.2016.04.038
Dymova L, Sevastjanov P, Tikhonenko A (2013) A direct interval extension of topsis method. Expert Syst Appl 40(12):4841–4847. https://doi.org/10.1016/j.eswa.2013.02.022
Farhadinia B (2013) Information measures for hesitant fuzzy sets and interval-valued hesitant fuzzy sets. Inf Sci 240:129–144. https://doi.org/10.1016/j.ins.2013.03.034
Gao H, Zhang H, Liu P (2019) Multi-attribute decision making based on intuitionistic fuzzy power Maclaurin symmetric mean operators in the framework of Dempster–Shafer theory. Symmetry 11(6):1–29. https://doi.org/10.3390/sym11060807
Garg H, Arora R (2018) Dual hesitant fuzzy soft aggregation operators and their application in decision-making. Cogn Comput 10(5):769–789. https://doi.org/10.1007/s12559-018-9569-6
Garg H, Arora R (2020a) Maclaurin symmetric mean aggregation operators based on t-norm operations for the dual hesitant fuzzy soft set. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-019-01238-w
Garg H, Arora R (2020b) Topsis method based on correlation coefficient for solving decision-making problems with intuitionistic fuzzy soft set information. AIMS Math 5(4):2944–2966. https://doi.org/10.3934/math.2020190
Garg H, Nancy (2020) Algorithms for single valued neutral decision making based on TOPSIS and clustering methods with new distance measure. Aims Math 5(3):2671–2693. https://doi.org/10.3934/math.2020173
He Y, He Z (2015) Extensions of atanassov’s intuitionistic fuzzy interaction bonferroni means and their application to multiple attribute decision making. IEEE Trans Fuzzy Syst 24(3):558–573. https://doi.org/10.1109/TFUZZ.2015.2460750
Jana C, Pal M, Wang J (2019) Bipolar fuzzy Dombi aggregation operators and its application in multiple-attribute decision-making process. J Ambient Intell Human Comput 10:3533–3549. https://doi.org/10.1007/s12652-018-1076-9
Jousselme AL, Grenier D, Éloi B (2001) A new distance between two bodies of evidence. Inf Fusion 2(2):91–101. https://doi.org/10.1016/S1566-2535(01)00026-4
Karaaslan F, Özlü Ş (2020) Correlation coefficients of dual type-2 hesitant fuzzy sets and their applications in clustering analysis. Int J Intell Syst. https://doi.org/10.1002/int.22239
Karamaz F, Karaaslan F (2020) Hesitant fuzzy parameterized soft sets and their applications in decision making. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-020-02258-7
Lai Y-J, Liu T-Y, Hwang C-L (1994) TOPSIS for MODM. Eur J Oper Res 76(3):486–500. https://doi.org/10.1016/0377-2217(94)90282-8
Liao H, Xu Z (2013) A VIKOR-based method for hesitant fuzzy multi-criteria decision making. Fuzzy Optim Decis Making 12(4):373–392. https://doi.org/10.1007/s10700-013-9162-0
Liu P, Chen S-M (2017) Group decision making based on heronian aggregation operators of intuitionistic fuzzy numbers. IEEE Trans Cybern 47(9):2514–2530. https://doi.org/10.1109/TCYB.2016.2634599
Liu P, Gao H (2019) Some intuitionistic fuzzy power Bonferroni mean operators in the framework of Dempster–Shafer theory and their application to multicriteria decision making. Appl Soft Comput 85:105790. https://doi.org/10.1016/j.asoc.2019.105790
Liu P, Li Y (2019) Multi-attribute decision making method based on generalized Maclaurin symmetric mean aggregation operators for probabilistic linguistic information. Comput Ind Eng 131:282–294. https://doi.org/10.1016/j.cie.2019.04.004
Liu P, You X (2020) Linguistic neutrosophic partitioned maclaurin symmetric mean operators based on clustering algorithm and their application to multi-criteria group decision-making. Artif Intell Rev 53:2131–2170. https://doi.org/10.1007/s10462-019-09729-0
Liu P, Zhang X (2018) Approach to multi-attributes decision making with intuitionistic linguistic information based on Dempster–Shafer evidence theory. IEEE Access 6:52969–52981. https://doi.org/10.1109/ACCESS.2018.2869844
Liu P, Zhang X (2020) A new hesitant fuzzy linguistic approach for multiple attribute decision making based on Dempster–Shafer evidence theory. Appl Soft Comput 86:105897. https://doi.org/10.1016/j.asoc.2019.105897
Liu C, Tang G, Liu P, Liu C (2019) Hesitant fuzzy linguistic archimedean aggregation operators in decision making with the Dempster–Shafer belief structure. Int J Fuzzy Syst 21(5):1330–1348. https://doi.org/10.1007/s40815-019-00660-8
Liu P, Chen S-M, Wang P (2020a) Multiple-attribute group decision-making based on q-rung orthopair fuzzy power Maclaurin symmetric mean operators. IEEE Trans Syst Man Cybern Syst 50(10):3741–3756. https://doi.org/10.1109/TSMC.2018.2852948
Liu P, Chen S-M, Wang Y (2020b) Multiattribute group decision making based on intuitionistic fuzzy partitioned maclaurin symmetric mean operators. Inf Sci 512:830–854. https://doi.org/10.1016/j.ins.2019.10.013
Liu P, Liu X, Ma G, Liang Z, Wang C, Alsaadi FE (2020c) A multi-attribute group decision-making method based on linguistic intuitionistic fuzzy numbers and Dempster–Shafer evidence theory. Int J Inf Technol Decis Making 19(2):499–524. https://doi.org/10.1142/S0219622020500042
Liu P, Zhang X, Wang Z, Shi Y (2020d) An extended vikor method for multiple attribute decision making with linguistic d numbers based on fuzzy entropy. Int J Inf Technol Decis Making 19(1):143–167. https://doi.org/10.1142/S0219622019500433
Lu X-S, Zhou M-C, Wu K (2019) A novel fuzzy logic-based text classification method for tracking rare events on twitter. IEEE Trans Syst Man Cybern Syst 99:1–10. https://doi.org/10.1109/TSMC.2019.2932436
Maclaurin C (1730) A second letter to Martin Folkes, Esq concerning the roots of equations, with demonstration of other rules of algebra. Philos Trans 36:59–96
Meng F, Xu Y, Wang N (2020) Correlation coefficients of dual hesitant fuzzy sets and their application in engineering management. J Ambient Intell Human Comput 11:2943–2961. https://doi.org/10.1007/s12652-019-01435-7
Mokhtia M, Eftekhari M, Saberi-Movahed F (2020) Feature selection based on regularization of sparsity based regression models by hesitant fuzzy correlation. Appl Soft Comput J 91:106255. https://doi.org/10.1016/j.asoc.2020.106255
Peng D-H, Gao C-Y, Gao Z-F (2013) Generalized hesitant fuzzy synergetic weighted distance measures and their application to multiple criteria decision-making. Appl Math Model 37(8):5837–5850. https://doi.org/10.1016/j.apm.2012.11.016
Peng D, Peng B, Wang T (2020) Reconfiguring IVHF-TOPSIS decision making method with parameterized reference solutions and a novel distance for corporate carbon performance evaluation. J Ambient Intell Human Comput 11:3811–3832. https://doi.org/10.1007/s12652-019-01603-9
Qian G, Wang H, Feng X (2013) Generalized hesitant fuzzy sets and their application in decision support system. Knowl Based Syst 37:357–365. https://doi.org/10.1016/j.knosys.2012.08.019
Qin J, Liu X (2014) An approach to intuitionistic fuzzy multiple attribute decision making based on Maclaurin symmetric mean operators. J Intell Fuzzy Syst 27(5):2177–2190. https://doi.org/10.3233/IFS-141182
Qin J, Liu X, Pedrycz W (2015) Hesitant fuzzy maclaurin symmetric mean operators and its application to multiple-attribute decision making. Int J Fuzzy Syst 17(4):509–520. https://doi.org/10.1007/s40815-015-0049-9
Qin Y, Cui X, Huang M, Zhong Y, Tang Z, Shi P (2019) Archimedean muirhead aggregation operators of q-Rung orthopair fuzzy numbers for multicriteria group decision making. Complexity 2019:3103741. https://doi.org/10.1155/2019/3103741
Qin Y, Cui X, Huang M, Zhong Y, Tang Z, Shi P (2020a) Linguistic interval-valued intuitionistic fuzzy archimedean power muirhead mean operators for multiattribute group decision-making. Complexity 2020:2373762. https://doi.org/10.1155/2020/2373762
Qin Y, Cui X, Huang M, Zhong Y, Tang Z, Shi P (2020b) Multiple-attribute decision-making based on picture fuzzy Archimedean power Maclaurin symmetric mean operators. Granul Comput. https://doi.org/10.1007/s41066-020-00228-0
Qin Y, Qi Q, Shi P, Scott PJ, Jiang X (2020c) Novel operational laws and power Muirhead mean operators ofpicture fuzzy values in the framework of Dempster–Shafer theory for multiple criteria decision making. Comput Ind Eng 149(11):106853. https://doi.org/10.1016/j.cie.2020.106853
Ren Z, Liao H, Liu Y (2020) Generalized Z-numbers with hesitant fuzzy linguistic information and its application to medicine selection for the patients with mild symptoms of the COVID-19. Comput Ind Eng 145:106517. https://doi.org/10.1016/j.cie.2020.106517
Rouhbakhsh FF, Ranjbar M, Effati S, Hassanpour H (2020) Multi objective programming problem in the hesitant fuzzy environment. Appl Intell. https://doi.org/10.1007/s10489-020-01682-8
Şahin R, Altun F (2020) Decision making with MABAC method under probabilistic single-valued neutrosophic hesitant fuzzy environment. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-020-01699-4
Sevastjanov P, Dymova L (2015) Generalised operations on hesitant fuzzy values in the framework of Dempster–Shafer theory. Inf Sci 311:39–58.https://doi.org/10.1016/j.ins.2015.03.041
Shafer G (1976) A mathematical theory of evidence. Princeton University Press, Princeton
Torra V (2010) Hesitant fuzzy sets. Int J Intell Syst 25(6):529–539. https://doi.org/10.1002/int.20418
Torra V, Narukawa Y (2009) On hesitant fuzzy sets and decision. In: Proceedings of the 2009 IEEE International Conference on Fuzzy Systems. IEEE, pp 1378–1382. https://doi.org/10.1109/FUZZY.2009.5276884
Ullah K, Garg H, Mahmood T, Jan N, Ali Z (2020) Correlation coefficients for t-spherical fuzzy sets and their applications in clustering and multi-attribute decision making. Soft Comput 24(3):1647–1659. https://doi.org/10.1007/s00500-019-03993-6
Wang YM, Elhag TMS (2006) On the normalization of interval and fuzzy weights. Fuzzy Sets Syst 157(18):2456–2471. https://doi.org/10.1016/j.fss.2006.06.008
Wang L, Shen Q, Zhu L (2016) Dual hesitant fuzzy power aggregation operators based on Archimedean t-conorm and t-norm and their application to multiple attribute group decision making. Appl Soft Comput 38:23–50. https://doi.org/10.1016/j.asoc.2015.09.012
Wei G (2012) Hesitant fuzzy prioritized operators and their application to multiple attribute decision making. Knowl Based Syst 31:176–182
Wei G, Zhao X, Lin R (2013) Some hesitant interval-valued fuzzy aggregation operators and their applications to multiple attribute decision making. Knowl Based Syst 46:43–53. https://doi.org/10.1016/j.knosys.2013.03.004
Xia M, Xu Z (2011) Hesitant fuzzy information aggregation in decision making. Int J Approx Reason 52(3):395–407. https://doi.org/10.1016/j.ijar.2010.09.002
Xu Z, Xia M (2011a) Distance and similarity measures for hesitant fuzzy sets. Inf Sci 181(11):2128–2138. https://doi.org/10.1016/j.ins.2011.01.028
Xu Z, Xia M (2011b) On distance and correlation measures of hesitant fuzzy information. Int J Intell Syst 26(5):410–425. https://doi.org/10.1002/int.20474
Xu Z, Xia M (2012) Hesitant fuzzy entropy and cross-entropy and their use in multiattribute decision-making. Int J Intell Syst 27(9):799–822. https://doi.org/10.1002/int.21548
Xu Z, Yager RR (2010) Power-geometric operators and their use in group decision making. IEEE Trans Fuzzy Syst 18(1):94–105. https://doi.org/10.1109/TFUZZ.2009.2036907
Xu Z, Yager RR (2011) Intuitionistic fuzzy bonferroni means. IEEE Trans Syst Man Cybern Part B (Cybern) 41(2):568–578. https://doi.org/10.1109/tsmcb.2010.2072918
Yager RR (2001) The power average operator. IEEE Trans Syst Man Cybern Part A Syst Humans Hum 31(6):724–731. https://doi.org/10.1109/3468.983429
Zadeh LA (1965) Fuzzy sets. Inf Control 8(3):338–353. https://doi.org/10.1016/S0019-9958(65)90241-X
Zhang Z (2013a) Generalized atanassov’s intuitionistic fuzzy power geometric operators and their application to multiple attribute group decision making. Inf Fusion 14(4):460–486. https://doi.org/10.1016/j.inffus.2013.02.001
Zhang Z (2013b) Hesitant fuzzy power aggregation operators and their application to multiple attribute group decision making. Inf Sci 234(Complete):150–181. https://doi.org/10.1016/j.ins.2013.01.002
Zhang N, Wei G (2013) Extension of VIKOR method for decision making problem based on hesitant fuzzy set. Appl Math Model 37(7):4938–4947. https://doi.org/10.1016/j.apm.2012.10.002
Zhang C, Wang C, Zhang Z et al (2019) A novel technique for multiple attribute group decision making in interval-valued hesitant fuzzy environments with incomplete weight information. J Ambient Intell Human Comput 10:2417–2433. https://doi.org/10.1007/s12652-018-0912-2
Zhu B, Xu Z, Xia M (2012) Hesitant fuzzy geometric Bonferroni means. Inf Sci 205:72–85. https://doi.org/10.1016/j.ins.2012.01.048
Zhu C, Zhu L, Zhang X (2016) Linguistic hesitant fuzzy power aggregation operators and their applications in multiple attribute decision-making. Inf Sci 367–368:809–826. https://doi.org/10.1016/j.ins.2016.07.011
Acknowledgements
This work was supported by the National Natural Science Foundation of China (No. 62033001), the Guangxi Colleges and Universities Key Laboratory of Intelligent Processing of Computer Images and Graphics (No. GIIP201703), and the Innovation Key Project of Guangxi Province (No. AA18118039-2)
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors state that they have no conflict of interest.
Ethical standard
This article does not contain any studies with human participants or animals performed by any of the authors.
Informed consent
Informed consent was taken from all individual participants included in the study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Zhong, Y., Cao, L., Zhang, H. et al. Hesitant fuzzy power Maclaurin symmetric mean operators in the framework of Dempster–Shafer theory for multiple criteria decision making. J Ambient Intell Human Comput 13, 1777–1797 (2022). https://doi.org/10.1007/s12652-021-02932-4
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-021-02932-4