Abstract
The hesitant fuzzy set permits the membership degree of an element to be a set of several possible values between 0 and 1, and is therefore an efficient tool for handling multi-criteria group decision making (MCGDM) problems in which experts hesitate between several values to assess an alternative. The aim of this paper is to study MCGDM problems in which the criterion values provided by experts take the form of hesitant fuzzy elements, and the weight information about both the decision makers and the criteria is unknown. By minimizing the divergence among the individual hesitant fuzzy decision matrices, we first establish a nonlinear optimization model to obtain an exact formula, from which the weights of decision makers can be derived. Then, based on all the individual hesitant fuzzy decision matrices, we construct a nonlinear optimization model to determine the weights of criteria by maximizing group consensus. After obtaining the weights of decision makers and criteria, a simple additive weighting operator is used to aggregate all the individual hesitant fuzzy decision matrices into the collective hesitant fuzzy decision matrix and is used to obtain the collective overall hesitant fuzzy values corresponding to each alternative. Moreover, all the above results are also extended to interval-valued hesitant fuzzy situations. Finally, we apply the developed models to an investment selection problem.
Similar content being viewed by others
Explore related subjects
Discover the latest articles and news from researchers in related subjects, suggested using machine learning.References
Atanassov, K.: Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20, 87–96 (1986)
Atanassov, K., Gargov, G.: Interval valued intuitionistic fuzzy sets. Fuzzy Sets Syst. 31, 343–349 (1989)
Bazaraa, M.S., Shetty, C.M.: Nonlinear Programming-Theory and Algorithms. Wiley, Singapore (1990)
Chen, N., Xu, Z.S., Xia, M.M.: Correlation coefficients of hesitant fuzzy sets and their applications to clustering analysis. Appl. Math. Model. 37(4), 2197–2211 (2013)
Chen, N., Xu, Z.S., Xia, M.M.: Interval-valued hesitant preference relations and their applications to group decision making. Knowledge-Based Syst. 37, 528–540 (2013)
Dubois, D., Prade, H.: Fuzzy Sets and Systems: Theory and Applications. Academic Press, New York (1980)
Herrera, F., Herrera-Viedma, E.: Linguistic decision analysis: steps for solving decision problems under linguistic information. Fuzzy Sets Syst. 115(1), 67–82 (2000)
Hu, J.H., Zhang, X.L., Chen, X.H., Liu, Y.M.: Hesitant fuzzy information measures and their applications in multi-criteria decision making. Int. J. Syst. Sci. 47(1), 62–76 (2016)
Li, L.G., Peng, D.H.: Interval-valued hesitant fuzzy Hamacher synergetic weighted aggregation operators and their application to shale gas areas selection. Math. Probl. Eng. 2014, Article ID 181050 (2014)
Liao, H.C., Xu, Z.S.: Extended hesitant fuzzy hybrid weighted aggregation operators and their application in decision making. Soft. Comput. 19(9), 2551–2564 (2015)
Liu, X.D., Zhu, J.J., Zhang, S.T., Hao, J.J., Liu, G.D.: Integrating LINMAP and TOPSIS methods for hesitant fuzzy multiple attribute decision making. J. Intell. Fuzzy Syst. 28(1), 257–269 (2015)
Ma, J., Fan, Z.P., Jiang, Y.P., Mao, J.Y.: An optimization approach to multiperson decision making based on different formats of preference information. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 36(5), 876–889 (2006)
Meng, F.Y., Chen, X.H., Zhang, Q.: Generalized hesitant fuzzy generalized shapley-choquet integral operators and their application in decision making. Int. J. Fuzzy Syst. 16(3), 400–410 (2014)
Miyamoto, S.: Remarks on basics of fuzzy sets and fuzzy multisets. Fuzzy Sets Syst. 156, 427–431 (2005)
Pei, Z., Yi, L.: A note on operations of hesitant fuzzy sets. Int. J. Comput. Intell. Syst. 8(2), 226–239 (2015)
Qin, J.D., Liu, X.W., Pedrycz, W.: Hesitant fuzzy Maclaurin symmetric mean operators and its application to multiple-attribute decision making. Int. J. Fuzzy Syst. 17(4), 509–520 (2015)
Rodríguez, R.M., Martínez, L., Torra, V., Xu, Z.S., Herrera, F.: Hesitant fuzzy sets: state of the art and future directions. Int. J. Intell. Syst. 29(6), 495–524 (2014)
Sevastjanov, P., Dymova, L.: Generalised operations on hesitant fuzzy values in the framework of Dempster-Shafer theory. Inf. Sci. 311, 39–58 (2015)
Tan, C.Q., Yi, W.T., Chen, X.H.: Hesitant fuzzy Hamacher aggregation operators for multicriteria decision making. Appl. Soft Comput. 26, 325–349 (2015)
Torra, V.: Hesitant fuzzy sets. Int. J. Intell. Syst. 25, 529–539 (2010)
Wang, Y.M.: Using the method of maximizing deviations to make decision for multi-indices. Syst. Eng. Electr. 7, 24–26 (1998)
Wang, J., Wang, J.Q., Zhang, H.Y., Chen, X.H.: Multi-criteria group decision-making approach based on 2-tuple linguistic aggregation operators with multi-hesitant fuzzy linguistic information. Int. J. Fuzzy Syst. 18(1), 81–97 (2016)
Wu, Z.B., Chen, Y.H.: The maximizing deviation method for group multiple attribute decision making under linguistic environment. Fuzzy Sets Syst. 158, 1608–1617 (2007)
Xia, M.M., Xu, Z.S.: Hesitant fuzzy information aggregation in decision making. Int. J. Approx. Reason. 52, 395–407 (2011)
Xu, Z.S.: Induced uncertain linguistic OWA operators applied to group decision making. Inf. Fusion 7(2), 231–238 (2006)
Xu, Z.S., Da, Q.L.: The uncertain OWA operator. Int. J. Intell. Syst. 17, 569–575 (2002)
Xu, Z.S., Hu, H.: Projection models for intuitionistic fuzzy multiple attribute decision making. Int. J. Inf. Technol. Decis. Mak. 9, 267–280 (2010)
Xu, Z.S., Xia, M.M.: Distance and similarity measures for hesitant fuzzy sets. Inf. Sci. 181, 2128–2138 (2011)
Xu, Z.S., Zhang, X.L.: Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information. Knowledge-Based Syst. 52, 53–64 (2013)
Yu, D.J.: Group decision making under multiplicative hesitant fuzzy environment. Int. J. Fuzzy Syst. 16(2), 233–241 (2014)
Yu, D.J.: Some hesitant fuzzy information aggregation operators based on Einstein operational laws. Int. J. Intell. Syst. 29(4), 320–340 (2014)
Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning, Part 1. Inf. Sci. 8, 199–249 (1975)
Zhang, Z.M., Wang, C., Tian, D.Z., Li, K.: Induced generalized hesitant fuzzy operators and their application to multiple attribute group decision making. Comput. Ind. Eng. 67, 116–138 (2014)
Zhang, Z.M., Wu, C.: Some interval-valued hesitant fuzzy aggregation operators based on Archimedean t-norm and t-conorm with their application in multi-criteria decision making. J. Intell. Fuzzy Syst. 27(6), 2737–2748 (2014)
Zhao, N., Xu, Z.S., Ren, Z.L.: On typical hesitant fuzzy prioritized “or” operator in multi-attribute decision making. Int. J. Intell. Syst. 31(1), 73–100 (2016)
Zhou, X.Q., Li, Q.G.: Generalized hesitant fuzzy prioritized Einstein aggregation operators and their application in group decision making. Int. J. Fuzzy Syst. 16(3), 303–316 (2014)
Acknowledgments
The author thanks the anonymous referees for their valuable suggestions in improving this paper. This work is supported by the National Natural Science Foundation of China (Grant No. 61375075), the Natural Science Foundation of Hebei Province of China (Grant No. F2012201020), and the Scientific Research Project of Department of Education of Hebei Province of China (Grant No. QN2016235).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhang, Z. Hesitant Fuzzy Multi-Criteria Group Decision Making with Unknown Weight Information. Int. J. Fuzzy Syst. 19, 615–636 (2017). https://doi.org/10.1007/s40815-016-0190-0
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40815-016-0190-0