Volume 24 , Issue 1 , PP: 281-295, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Murugan Palanikumar 1 , Lejo J. Manavalan 2 , T. T. Raman 3 , Aiyared Iampan 4 *
Doi: https://doi.org/10.54216/IJNS.240125
This article discusses a new approach to multiple attribute decision-making (MADM) based on sine trigonometric (ST) (l1, l2, l3) neutrosophic sets (NS). We discuss the concept of ST (l1, l2, l3) neutrosophic weighted averaging (NWA), ST (l1, l2, l3) neutrosophic weighted geometric (NWG), ST (l1, l2, l3) generalized neutrosophic weighted averaging (GNWA) and ST (l1, l2, l3) generalized neutrosophic weighted geometric (GNWG). We presented during our discussion showed an algorithm that used these operators. Extensive Hamming distances are illustrated numerically. Also included in this communication are discussions of idempotency, boundness, commutativity, and monotonicity for ST (l1, l2, l3) neutrosophic sets. By using them, you can find the best option faster, easier, and more conveniently. As a result, ST (l1, l2, l3) and more precise conclusions are more closely related. A comparison is made between some current models and those proposed to demonstrate the dependability and utility of the current models. Furthermore, fascinating findings were revealed in the study.
Aggregating operator , decision making , STNWA , STNWG , STGNWA and STGNWG.
[1] L. A. Zadeh, Fuzzy sets, Information and control, 8(3), (1965), 338-353.
[2] K. Atanassov, Intuitionistic fuzzy sets, Fuzzy sets and Systems, 20(1), (1986), 87-96.
[3] R. R. Yager, Pythagorean membership grades in multi criteria decision-making, IEEE Trans. Fuzzy Systems, 22, (2014), 958-965.
[4] S. Ashraf, S. Abdullah, T. Mahmood, F. Ghani and T. Mahmood, Spherical fuzzy sets and their applications in multi-attribute decision making problems, Journal of Intelligent and Fuzzy Systems, 36, (2019), 2829-284.
[5] B.C. Cuong and V. Kreinovich, Picture fuzzy sets a new concept for computational intelligence problems, in Proceedings of 2013 Third World Congress on Information and Communication Technologies (WICT 2013), IEEE, (2013), 1-6.
[6] P. Liu, G. Shahzadi, M. Akram, Specific types of picture fuzzy Yager aggregation operators for decisionmaking, International Journal of Computational Intelligence Systems, 13(1), (2020), 1072-1091.
[7] W.F. Liu, J. Chang, X. He, Generalized Pythagorean fuzzy aggregation operators and applications in decision making, Control Decis. 31, (2016), 2280-2286.
[8] X. Peng, and Y. Yang, Fundamental properties of interval valued Pythagorean fuzzy aggregation operators, International Journal of Intelligent Systems, (2015), 1-44.
[9] K.G. Fatmaa, K. Cengiza, Spherical fuzzy sets and spherical fuzzy TOPSIS method, Journal of Intelligent and Fuzzy Systems, 36(1), (2019), 337-352.
[10] R.N. Xu and C.L. Li, Regression prediction for fuzzy time series, Appl. Math. J. Chinese Univ., 16, (2001), 451-461.
[11] Z. Xu, R.R. Yager, Some geometric aggregation operators based on intuitionistic fuzzy sets, Int. J. Gen. Syst. 35, (2006), 417-433.
[12] D.F. Li, Multi-attribute decision making method based on generalized OWA operators with intuitionistic fuzzy sets, Expert Syst. Appl. 37, (2010), 8673-8678.
[13] S. Zeng, W. Sua, Intuitionistic fuzzy ordered weighted distance operator, Knowl. Based Syst. 24, (2011), 1224-1232.
[14] X. Peng, H. Yuan, Fundamental properties of Pythagorean fuzzy aggregation operators, Fundam. Inform. 147, (2016), 415-446.
[15] S. Ashraf, S. Abdullah, T. Mahmood, Spherical fuzzy Dombi aggregation operators and their application in group decision making problems, J. Amb. Intell. Hum. Comput. 11, (2020), 2731-2749.
[16] M Palanikumar, K Arulmozhi, MCGDM based on TOPSIS and VIKOR using Pythagorean neutrosophic soft with aggregation operators, Neutrosophic Sets and Systems,, 538-555, 2022.
