MCDM Problem Under Single-Valued Neutrosophic Numbers Based on a Novel Similarity Measure
Madineh Farnam
1
(
Department of Electrical Engineering, Shohadaye Hoveizeh Campus of Technology, Shahid Chamran University of Ahvaz, Dasht-e Azadegan, Khuzestan, Iran.
)
Majid Darehmiraki
2
(
Department of Mathematics and Statistics, Faculty of Data Sciences and Energy, Behbahan Khatam Alanbia University of Technology, Behbahan, Iran.
)
الکلمات المفتاحية: Neutrosophic set, Single-valued Neutrosophic number, Ranking methods, Similarity measure, Multi-criteria decision making.,
ملخص المقالة :
One of the challenges in MCDM with a neutrosophic environment is the lack of an efficient analysis tool to rank the alternatives. The effective ranking of alternatives in MCDM under a neutrosophic environment presents a significant challenge due to the absence of robust analytical tools. Bridging this gap is essential for enhancing decision-making processes across various practical applications. Aggregative operators, ranking methods, distance measures, and similarity measures are among the most essential tools for sorting fuzzy data and their extensions, including Neutrosophic numbers. However, existing methods often exhibit significant shortcomings, such as contradictory results under certain conditions, and computational inefficiency. For example, Deli and Subas’s approach and Ye’s approach may yield contradicting results for specific instances of single-valued trapezoidal neutrosophic (SVTriN) numbers. The novel similarity measure proposed in this study introduces a new mathematical formulation that enhances the meaningfulness and conceptual soundness of the analysis by effectively capturing the intrinsic indeterminacy of neutrosophic numbers. Unlike existing methods, it provides consistent results across various scenarios, eliminating contradictory outcomes. This innovative approach deepens the understanding of relationships between alternatives, making it highly suitable for practical implementation in MCDM problems. On the other hand, very few papers have used the similarity measure to sort the alternatives in the MCDM problem under trapezoidal neutrosophic numbers. Thus, the main objective of this study is to introduce a novel similarity measure for sorting alternatives. For this purpose, we first highlight some shortcomings related to the existing ranking approach for neutrosophic numbers. After introducing the novel similarity measure, several critical properties of the suggested similarity measure between neutrosophic numbers are investigated. The proposed similarity measure offers a proper way to apply the TOPSIS method in the context of neutrosophic information. The efficiency and utility of the proposed similarity measure are illustrated by a comparative example.
[1] Smarandache F. A unifying field in Logics: Neutrosophic Logic. Neutrosophy, Neutrosophic Set, Neutrosophic Probability. Rehoboth: American Research Press; 1998.
[2] Sarannya R, Kalayathankal SJ, George M, Smarandache F. n-Cylindrical Fuzzy Neutrosophic Topological Spaces. Journal of Fuzzy Extension and Applications. 2023; 4(2): 141-147. DOI: http://doi.org/10.22105/jfea.2022.365810.1234
[3] Kumari RS, Kalayathankal SJ, George M, Smarandache F. On some related concepts n-cylindrical fuzzy neutrosophic topological spaces. Journal of Fuzzy Extension and Applications. 2023; 4(1): 40-51. DOI: http://doi.org/10.22105/jfea.2023.377520.1240
[4] Das SK. Application of transportation problem under pentagonal neutrosophic environment. Journal of Fuzzy Extension and Applications. 2020; 1(1): 27-41. DOI: http://doi.org/10.22105/jfea.2020.246633.1001
[5] Duran V, Topal S, Smarandache F. An application of neutrosophic logic in the confirmatory data analysis of the satisfaction with life scale. Journal of Fuzzy Extension and Applications. 2021; 2(3): 262-282. DOI: http://doi.org/10.22105/jfea.2021.280497.1100
[6] Kumar R, Edalatpanah SA, Jha S, Broumi S, Singh R, Dey A. A multi objective programming approach to solve integer valued neutrosophic shortest path problems. Neutrosophic Sets and Systems. 2019; 24(13): 134-149. DOI: http://doi.org/10.5281/zenodo.2595968
[7] Mondal K, Pramanik S. Neutrosophic decision making model for clay-brick selection in construction field based on grey relational analysis. Neutrosophic Sets and Systems. 2015; 9(11): 64-71. DOI: http://doi.org/10.5281/ZENODO.34864
[8] Mondal K, Pramanik S, Smarandache F. Several trigonometric Hamming similarity measures of rough neutrosophic sets and their applications in decision making. New trends in neutrosophic theory and application. 2016; 1: 93-103.
[9] Pramanik S, Dalapati S, Roy TK. Logistics center location selection approach based on neutrosophic multi-criteria decision making. New Trends in Neutrosophic Theory and Applications. 2016; 161-174.
[10] Yang W, Cai L, Edalatpanah SA, Smarandache F. Triangular single valued neutrosophic data envelopment analysis: application to hospital performance measurement. Symmetry. 2020; 12(4): 588. DOI: http://doi.org/10.3390/sym12040588
[11] Wang H, Smarandache F, Zhang Y, Sunderraman R. Single valued neutrosophic sets. Infinite study. 2010.
[12] Deli I, uba Y. Single valued neutrosophic numbers and their applications to multicriteria decision making problem. Neutrosophic Sets and Systems. 2014; 2(1): 1-13.
[13] Deli I, uba Y. A ranking method of single valued neutrosophic numbers and its applications to multiattribute decision making problems. International journal of machine learning and cybernetics. 2017; 8(4): 1309-1322. DOI: http://doi.org/10.1007/s13042016-0505-3
[14] Pramanik S, Dey PP, Giri BC. TOPSIS for single valued neutrosophic soft expert set based multi-attribute decision making problems. Neutrosophic Sets and Systems. 2015; 10: 88-95. DOI: http://doi.org/10.5281/zenodo.571238
[15] Wang J, Wang J-q, Ma Y-x. Possibility degree and power aggregation operators of single-valued trapezoidal neutrosophic numbers and applications to multi-criteria group decision-making. Cognitive Computation. 2021; 13: 657-672. DOI: http://doi.org/10.1007/s12559-020-09736-2
[16] Ye J. Some weighted aggregation operators of trapezoidal neutrosophic numbers and their multiple attribute decision making method. Informatica. 2017; 28(2): 387-402.
[17] Biswas P, Pramanik S, Giri BC. TOPSIS strategy for multi-attribute decision making with trapezoidal neutrosophic numbers. Neutrosophic Sets and Systems. 2018; 19: 29-39. DOI: https://doi.org/10.5281/zenodo.1235335
[18] Liang R-x, Wang J-q, Zhang H-y. A multi-criteria decision-making method based on single-valued trapezoidal neutrosophic preference relations with complete weight information. Neural Computing and Applications. 2018; 30: 3383-3398. DOI: http://doi.org/10.1007/s00521- 017-2925-8
[19] Liang R, Wang J, Zhang H. Evaluation of e-commerce websites: An integrated approach under a single-valued trapezoidal neutrosophic environment. Knowledge-based systems. 2017; 135: 44-59. DOI: https://doi.org/10.1016/j.knosys.2017.08.002
[20] Pramanik S, Mallick R. VIKOR based MAGDM strategy with trapezoidal neutrosophic numbers. Neutrosophic Sets and Systems. 2018; 22: 118-130. DOI: http://doi.org/10.5281/zenodo.2160840
[21] Zeng S, Luo D, Zhang C, Li X. A correlation-based TOPSIS method for multiple attribute decision making with single-valued neutrosophic information. International Journal of Information Technology & Decision Making. 2020; 19(01): 343-358. DOI: http://doi.org/10.1142/S0219622019500512
[22] Said B, Lathamaheswari M, Tan R, Nagarajan D, Mohamed T, Smarandache F, Bakali A. A new distance measure for trapezoidal fuzzy neutrosophic numbers based on the centroids. Neutrosophic Sets and Systems. 2020; 35: 478-502. DOI: http://doi.org/10.5281/zenodo.3951706
[23] Garai T, Garg H, Roy TK. A ranking method based on possibility mean for multi-attribute decision making with single valued neutrosophic numbers. Journal of Ambient Intelligence and Humanized Computing. 2020; 11: 5245-5258. DOI: https://doi.org/10.1007/s12652-020-01853-y
[24] Xu D, Peng L. An improved method based on TODIM and TOPSIS for multi-attribute decision-making with multi-valued neutrosophic sets. Computer Modeling in Engineering & Sciences. 2021; 129(2): 907- 926. DOI: http://doi.org/10.32604/cmes.2021.016720
[25] Rdvan , Fuat A, Gke Dilek K. A singlevalued neutrosophic multicriteria group decision approach with DPLTOPSIS method based on optimization. International Journal of Decision Support System Technology. 2021; 36(7): 3339-3366. DOI: http://doi.org/10.1002/int.22418
[26] Broumi S, Smarandache F. Several similarity measures of neutrosophic sets. Neutrosophic Sets and Systems. 2013; 1: 54-62. DOI: http://doi.org/10.6084/M9.FIGSHARE.1502610
[27] Ye J. Similarity measures between interval neutrosophic sets and their applications in multicriteria decision-making. Journal of intelligent & fuzzy systems. 2014; 26(1): 165-172. DOI: http://doi.org/10.3233/IFS-120724
[28] Ye S, Fu J, Ye J. Medical diagnosis using distance-based similarity measures of single valued neutrosophic multisets. Neutrosophic Sets and Systems. 2015; 7(1): 47-52. DOI: http://doi.org/10.5281/zenodo.571470
[29] uba Y. Neutrosophic numbers and their application to multi-attribute decision making problems (In Turkish). Masters Thesis, Kilis 7 Aralk University, Graduate School of Natural and Applied Science; 2018.
[30] Yang X. Research on the application of MADM in flood risk evaluation Doctoral dissertation. Wuhan, Huazhong University of Science and Technology; 2012.