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Abstract
Simplified neutrosophic sets (SNSs) can effectively solve the uncertainty problems, especially those involving the indeterminate and inconsistent information. Considering the advantages of SNSs, a new approach for multi-criteria decision-making (MCDM) problems is developed under the simplified neutrosophic environment. First, the prioritized weighted average operator and prioritized weighted geometric operator for simplified neutrosophic numbers (SNNs) are defined, and the related theorems are also proved. Then two novel effective cross-entropy measures for SNSs are proposed, and their properties are proved as well. Furthermore, based on the proposed prioritized aggregation operators and cross-entropy measures, the ranking methods for SNSs are established in order to solve MCDM problems. Finally, a practical MCDM example for coping with supplier selection of an automotive company is used to demonstrate the effectiveness of the developed methods. Moreover, the same example-based comparison analysis of between the proposed methods and other existing methods is carried out.
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Zadeh, L.A.: Fuzzy sets. Inf. Control8(3), 338–353 (1965)
Yager, R.R.: Multiple objective decision-making using fuzzy sets. Int. J. Man-Mach. Stud.9(4), 375–382 (1997)
Khatibi, V., Montazer, G.A.: Intuitionistic fuzzy set vs. fuzzy set application in medical pattern recognition. Artif. Intell. Med.47(1), 43–52 (2009)
Atanassov, K.T.: Intuitionistic fuzzy sets. Fuzzy Sets Syst.20(1), 87–96 (1986)
Gau, W.L., Buehrer, D.J.: Vague sets. IEEE Trans. Syst. Man Cybern.23(2), 610–614 (1993)
Liu, H.W., Wang, G.J.: Multi-criteria decision-making methods based on intuitionistic fuzzy sets. Eur. J. Oper. Res.179(1), 200–233 (2007)
Pei, Z., Zheng, L.: A novel approach to multi-attribute decision making based on intuitionistic fuzzy sets. Expert Syst. Appl.39(3), 2560–2566 (2012)
Yu, D.J.: Multi-criteria decision making based on generalized prioritized aggregation operators under intuitionistic fuzzy environment. Int. J. Fuzzy Syst.15(1), 47–54 (2013)
Tan, C.Q., Chen, X.H.: Dynamic similarity measures between intuitionistic fuzzy sets and its application. Int J Fuzzy Syst.16(4), 511–519 (2014)
Tao, Z.F., Chen, H.Y., Zhou, L.G., Liu, J.P.: A generalized multiple attributes group decision making approach based on intuitionistic fuzzy sets. Int. J. Fuzzy Syst.16(2), 184–195 (2014)
Wang, J.Q., Zhou, P., Li, K.J., Zhang, H.Y., Chen, X.H.: Multi-criteria decision-making method based on normal intuitionistic fuzzy-induced generalized aggregation operator. TOP22, 1103–1122 (2014)
Puri, J., Yadav, S.P.: Intuitionistic fuzzy data envelopment analysis: an application to the banking sector in India. Expert Syst. Appl.42(11), 4982–4998 (2015)
De, S.K., Biswas, R., Roy, A.R.: An application of intuitionistic fuzzy sets in medical diagnosis. Fuzzy Sets Syst.117(2), 209–213 (2001)
Shinoj, T.K., Sunil, J.J.: Intuitionistic fuzzy multisets and its application in medical diagnosis. Int. J. Math. Comput. Sci.6, 34–37 (2012)
Vlachos, I.K., Sergiadis, G.D.: Intuitionistic fuzzy information–applications to pattern recognition. Pattern Recognit. Lett.28(2), 197–206 (2007)
Li, D.F., Cheng, C.T.: New similarity measures of intuitionistic fuzzy sets and application to pattern recognitions. Pattern Recognit. Lett.23(1), 221–225 (2002)
Joshi, B.P., Kumar, S.: Fuzzy time series model based on intuitionistic fuzzy sets for empirical research in stock market. Int. J. Appl. Evol. Comput.3(4), 71–84 (2012)
Li, L., Yang, J., Wu, W.: Intuitionistic fuzzy hopfield neural network and its stability. Neural Netw. World21(5), 461–472 (2011)
Khatibi, V., Iranmanesh, H., Keramati, A.: A neuro-IFS intelligent system for marketing strategy selection. Innov. Comput. Technol.241, 61–70 (2011)
Atanassov, K.T., Gargov, G.: Interval valued intuitionistic fuzzy sets. Fuzzy Sets Syst.31(3), 343–349 (1989)
Yue, Z., Jia, Y.: An application of soft computing technique in group decision making under interval-valued intuitionistic fuzzy environment. Appl. Soft Comput.13(5), 2490–2503 (2013)
Yu, D.J., Merigó, J.M., Zhou, L.G.: Interval-valued multiplicative intuitionistic fuzzy preference relations. Int. J. Fuzzy Syst.15(4), 412–422 (2013)
Wang, J.Q., Han, Z.Q., Zhang, H.Y.: Multi-criteria group decision-making method based on intuitionistic interval fuzzy information. Group Decis. Negot.23(4), 715–733 (2014)
Wei, G.W.: Approaches to interval intuitionistic trapezoidal fuzzy multiple attribute decision making with incomplete weight information. Int. J. Fuzzy Syst.17(3), 484–489 (2015)
De Miguel, L., Bustince, H., Fernandez, J., Induráin, E., Kolesárová, A., Mesiar, R.: Construction of admissible linear orders for interval-valued Atanassov intuitionistic fuzzy sets with an application to decision making. Inf. Fusion27, 189–197 (2016)
Torra, V.: Hesitant fuzzy sets. Int. J. Intell. Syst.25(6), 529–539 (2010)
Chen, N., Xu, Z.S., Xia, M.M.: Interval-valued hesitant preference relations and their applications to group decision making. Knowl.-Based Syst.37, 528–540 (2013)
Wang, J.Q., Wu, J.T., Wang, J., Zhang, H.Y., Chen, X.H.: Multi-criteria decision-making methods based on the Hausdorff distance of hesitant fuzzy linguistic numbers. Soft. Comput.20(4), 1621–1633 (2016)
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)
Zhou, H., Wang, J., Zhang, H.Y., Chen, X.H.: Linguistic hesitant fuzzy multi-criteria decision-making method based on evidential reasoning. Int. J. Syst. Sci.47(2), 314–327 (2016)
Wang, J., Wang, J.Q., Zhang, H.Y., Chen, X.H.: Multi-criteria decision-making based on hesitant fuzzy linguistic term sets: an outranking approach. Knowl.-Based Syst.86, 224–236 (2015)
Tian, Z.P., Wang, J., Wang, J.Q., Chen, X.H.: Multi-criteria decision-making approach based on gray linguistic weighted Bonferroni mean operator. Int. Trans. Oper. Res. (2015). doi:10.1111/itor.12220
Peng, J.J., Wang, J.Q., Wu, X.H., Zhang, H.Y., Chen, X.H.: The fuzzy cross-entropy for intuitionistic hesitant fuzzy sets and its application in multi-criteria decision-making. Int. J. Syst. Sci.46(13), 2335–2350 (2015)
Wang, H., Smarandache, F., Zhang, Y.Q., Sunderraman, R.: Single valued neutrosophic sets. Multispace Multistruct4, 410–413 (2010)
Smarandache, F.: A unifying field in logics: neutrosophy: neutrosophic probability, set and logics. American Research Press, Rehoboth (1999)
Wang, H., Smarandache, F., Zhang, Y.Q., Sunderraman, R.: Interval neutrosophic sets and logic: theory and applications in computing. Hexis, Phoenix (2005)
Liu, P.D., Chu, Y.C., Li, Y.W., Chen, Y.B.: Some generalized neutrosophic number Hamacher aggregation operators and their application to group decision making. Int. J. Fuzzy Syst.16(2), 242–255 (2014)
Liu, P.D., Li, H.G.: Multiple attribute decision-making method based on some normal neutrosophic Bonferroni mean operators. Neural Comput. Appl. (2015). doi:10.1007/s00521-015-2048-z
Maji, P.K.: Weighted neutrosophic soft sets approach in a multi-criteria decision making problem. J. New Theory5, 1–12 (2015)
Peng, J.J., Wang, J.Q., Wu, X.H., Wang, J., Chen, X.H.: Multi-valued neutrosophic sets and power aggregation operators with their Applications in multi-criteria group decision-making problems. Int. J. Comput. Intell. Syst.8(2), 345–363 (2015)
Tian, Z.P., Wang, J., Zhang, H.Y., Chen, X.H., Wang, J.Q.: Simplified neutrosophic linguistic normalized weighted Bonferroni mean operator and its application to multi-criteria decision-making problems. Filomat (2015)
Guo, Y.H., Şengür, A., Tian, J.W.: A novel breast ultrasound image segmentation algorithm based on neutrosophic similarity score and level set. Comput. Methods Programs Biomed.123, 43–53 (2016)
Ye, J.: A multicriteria decision-making method using aggregation operators for simplified neutrosophic sets. J. Intell. Fuzzy Syst.26(5), 2459–2466 (2014)
Ye, J.: Single valued neutrosophic cross-entropy for multicriteria decision making problems. Appl. Math. Model.38(3), 1170–1175 (2014)
Ye, J.: Multicriteria decision-making method using the correlation coefficient under single-valued neutrosophic environment. Int. J. Gen Syst42(4), 386–394 (2013)
Tian, Z.P., Zhang, H.Y., Wang, J., Wang, J.Q., Chen, X.H.: Multi-criteria decision-making method based on a cross-entropy with interval neutrosophic sets. Int. J. Syst. Sci. (2015). doi:10.1080/00207721.2015.1102359
Zhang, H.Y., Ji, P., Wang, J., Chen, X.H.: Improved weighted correlation coefficient based on integrated weight for interval neutrosophic sets and its application in multi-criteria decision making problems. Int. J. Comput. Intell. Syst.8(6), 1027–1043 (2015)
Zhang, H.Y., Wang, J., Chen, X.H.: An outranking approach for multi-criteria decision-making problems with interval-valued neutrosophic sets. Neural Comput. Appl.27(3), 615–627 (2016)
Ye, J.: Vector similarity measures of simplified neutrosophic sets and their application in multicriteria decision making. Intern. J. Fuzzy Syst.16(2), 2204–2211 (2014)
Peng, J.J., Wang, J., Zhang, H.Y., Chen, X.H.: An outranking approach for multi-criteria decision-making problems with simplified neutrosophic sets. Appl. Soft Comput.25, 336–346 (2014)
Peng, J.J., Wang, J.Q., Wang, J., Zhang, H.Y., Chen, X.H.: Simplified neutrosophic sets and their applications in multi-criteria group decision-making problems. Int. J. Syst. Sci.47(10), 2342–2358 (2016)
Yager, R.R.: Prioritized aggregation operators. Int. J. Approx. Reason.48, 263–274 (2008)
Kullback, S.: Information theory and statistics. Wiley, New York (1959)
Shang, X.G., Jiang, W.S.: A note on fuzzy information measures. Pattern Recognit. Lett.18, 425–432 (1997)
Ho, W., Xu, X., Dey, P.K.: Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. Eur. J. Oper. Res.202(1), 16–24 (2010)
Boran, F.E.: A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Syst. Appl.36(8), 11363–11368 (2009)
Liu, P.D., Wang, Y.M.: Multiple attribute decision-making method based on single-valued neutrosophic normalized weighted Bonferroni mean. Neural Comput. Appl.25(7–8), 2001–2010 (2014)
Acknowledgments
The author would like to thank the editors and the anonymous referees for their valuable and constructive comments and suggestions that greatly help the improvement of this paper. This work is supported by the National Natural Science Foundation of China (Nos 71571193, 71271218, and 71431006).
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School of Business, Central South University, Changsha, 410083, People’s Republic of China
Xiao-hui Wu, Jian-qiang Wang, Juan-juan Peng & Xiao-hong Chen
School of Economics and Management, Hubei University of Automotive Technology, Shiyan, 442002, People’s Republic of China
Xiao-hui Wu & Juan-juan Peng
- Xiao-hui Wu
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- Jian-qiang Wang
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- Juan-juan Peng
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- Xiao-hong Chen
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Correspondence toJian-qiang Wang.
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Wu, Xh., Wang, Jq., Peng, Jj.et al. Cross-Entropy and Prioritized Aggregation Operator with Simplified Neutrosophic Sets and Their Application in Multi-Criteria Decision-Making Problems.Int. J. Fuzzy Syst.18, 1104–1116 (2016). https://doi.org/10.1007/s40815-016-0180-2
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