Aczel-Alsina Aggregation Operators Based on Complex Single-valued Neutrosophic Information and Their Application in Decision-Making Problems

Authors

  • Areeba Naseem Department of Mathematics, Riphah International University (Lahore Campus), 54000, Lahore, Pakistan
  • Maria Akram Department of Mathematics, Riphah International University (Lahore Campus), 54000, Lahore, Pakistan
  • Kifayat Ullah Department of Mathematics, Riphah International University (Lahore Campus), 54000, Lahore, Pakistan https://orcid.org/0000-0002-3350-6652
  • Zeeshan Ali Department of Mathematics & Statistics, International Islamic University Islamabad, 44000, Islamabad, Pakistan https://orcid.org/0000-0002-6745-9567

DOI:

https://doi.org/10.31181/dma11202312

Keywords:

Complex single-valued neutrosophic sets, Aczel-Alsina aggregation operators, Decision-making methods

Abstract

To develop the theory of aggregation operators based on the Aczel-Alsina t-norm and t-conorm is a very challenging task for individuals, where the idea of Aczel-Alsina norms is the modified version of the algebraic norms. The main theme of this manuscript is to evaluate the Aczel-Alsina operational laws and Aczel-Alsina aggregation operators for complex single-valued neutrosophic (CSVN) information such as CSVN Aczel-Alsina weighted averaging (CSVNAAWA), CSVN Aczel-Alsina ordered weighted averaging (CSVNAAOWA), CSVN Aczel-Alsina hybrid averaging (CSVNAAHA), CSVN Aczel-Alsina weighted geometric (CSVNAAWG), CSVN Aczel-Alsina ordered weighted geometric (CSVNAAOWG), CSVN Aczel-Alsina hybrid geometric (CSVNAAHG) operators, idempotency, monotonicity, and boundedness. Additionally, in the presence of the above-derived operators, we illustrated a model of the MADM “multi-attribute decision-making” procedure for CSVN values. Finally, we employed various numerical examples to demonstrate the supremacy and efficiency of the discovered theory to compare it with various prevailing operators.

Downloads

Download data is not yet available.

References

Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353. https://doi.org/10.1016/S0019-9958(65)90241-X

Atanassov, K. (1986). Intuitionistic fuzzy sets. Fuzzy sets and systems, 20 (1), 87-96. https://doi.org/10.1016/S0165-0114(86)80034-3

Smarandache, F. (1998). Neutrosophy. Neutrosophic Probability, Set, and Logic, ProQuest Information & Learning; LearnQuest: Ann Arbor, MI, USA.

Wang, H.; Smarandache, F.; Zhang, Y.Q.; Sunderraman, R. (2010). Single-valued neutrosophic sets. Multispace Multistruct, 4, 410–413.

Ye, J. (2014). Improved correlation coefficients of single valued neutrosophic sets and interval neutrosophic sets for multiple attribute decision making. Journal of Intelligent & Fuzzy Systems, 27(5), 2453-2462. https://doi.org/10.3233/IFS-141215

Yang, H. L., Zhang, C. L., Guo, Z. L., Liu, Y. L., & Liao, X. (2017). A hybrid model of single valued neutrosophic sets and rough sets: single valued neutrosophic rough set model. Soft Computing, 21(21), 6253-6267. https://doi.org/10.1007/s00500-016-2356-y

Ji, P., Wang, J. Q., & Zhang, H. Y. (2018). Frank prioritized Bonferroni mean operator with single-valued neutrosophic sets and its application in selecting third-party logistics providers. Neural Computing and Applications, 30(3), 799-823. https://doi.org/10.1007/s00521-016-2660-6

Garg, H. (2017). Some new biparametric distance measures on single-valued neutrosophic sets with applications to pattern recognition and medical diagnosis. Information, 8(4), 162-189. https://doi.org/10.3390/info8040162

Ashraf, S., Abdullah, S., & Smarandache, F. (2019). Logarithmic hybrid aggregation operators based on single valued neutrosophic sets and their applications in decision support systems. Symmetry, 11(3), 364-387. https://doi.org/10.3390/sym11030364

Garg, H. (2019). A novel divergence measure and its based TOPSIS method for multi criteria decision-making under single-valued neutrosophic environment. Journal of Intelligent & Fuzzy Systems, 36(1), 101-115. https://doi.org/10.3233/JIFS-18040

Saqlain, M., Jafar, N., Moin, S., Saeed, M., & Broumi, S. (2020). Single and multi-valued neutrosophic hypersoft set and tangent similarity measure of single valued neutrosophic hypersoft sets. Neutrosophic Sets and Systems, 32(1), 317-329. https://doi.org/10.5281/zenodo.3723165

Garg, H. (2019). Algorithms for possibility linguistic single-valued neutrosophic decision-making based on COPRAS and aggregation operators with new information measures. Measurement, 138, 278-290. https://doi.org/10.1016/j.measurement.2019.02.031

Saqlain, M., Jafar, M. N., & Riaz, M. (2020). A new approach of neutrosophic soft set with generalized Fuzzy TOPSIS in application of smart phone selection. Neutrosophic Sets and Systems, 32, 307-316. https://doi.org/10.5281/zenodo.3723161

Garg, H. (2020). Novel neutrality aggregation operator-based multiattribute group decision-making method for single-valued neutrosophic numbers. Soft Computing, 24(14), 10327-10349. https://doi.org/10.1007/s00500-019-04535-w

Riaz, M., Naeem, K., Zareef, I., & Afzal, D. (2020). Neutrosophic N-soft sets with TOPSIS method for multiple attribute decision making. Neutrosophic sets and systems, 32, 146-170. https://doi.org/10.5281/zenodo.3723131

Ramot, D., Milo, R., Friedman, M., & Kandel, A. (2002). Complex fuzzy sets. IEEE Transactions on Fuzzy Systems, 10(2), 171-186. https://doi.org/10.1109/91.995119

Alkouri, A. M. D. J. S., & Salleh, A. R. (2012). Complex intuitionistic fuzzy sets. In AIP conference proceedings, American Institute of Physics, 1482(1), 464-470. https://doi.org/10.1063/1.4757515

Ali, M., & Smarandache, F. (2017). Complex neutrosophic set. Neural Computing and Applications, 28(7), 1817-1834. https://doi.org/10.1007/s00521-015-2154-y

Mahmood, T., & Ali, Z. (2022). Prioritized Muirhead Mean Aggregation Operators under the Complex Single-Valued Neutrosophic Settings and Their Application in Multi-Attribute Decision-Making. Journal of Computational and Cognitive Engineering, 56-73. https://doi.org/10.47852/bonviewJCCE2022010104

Dat, L. Q., Thong, N. T., Ali, M., Smarandache, F., Abdel-Basset, M., & Long, H. V. (2019). Linguistic approaches to interval complex neutrosophic sets in decision making. IEEE access, 7, 38902-38917. https://doi.org/10.1109/ACCESS.2019.2902841

Al-Quran, A., & Alkhazaleh, S. (2018). Relations between the complex neutrosophic sets with their applications in decision making. Axioms, 7(3), 64-83. https://doi.org/10.3390/axioms7030064

Garg, H. (2018). Multi-criteria decision-making method based on prioritized Muirhead mean aggregation operator under neutrosophic set environment. Symmetry, 10(7), 280-307. https://doi.org/10.3390/sym10070280

Aczél, J., & Alsina, C. (1982). Characterizations of some classes of quasilinear functions with applications to triangular norms and to synthesizing judgements. aequationes mathematicae, 25(1), 313-315. https://doi.org/10.1007/BF02189626

Senapati, T., Chen, G., & Yager, R. R. (2022). Aczel–Alsina aggregation operators and their application to intuitionistic fuzzy multiple attribute decision making. International Journal of Intelligent Systems, 37(2), 1529-1551. https://doi.org/10.1002/int.22684

Sarfraz, M., Ullah, K., Akram, M., Pamucar, D., & Božanić, D. (2022). Prioritized Aggregation Operators for Intuitionistic Fuzzy Information Based on Aczel–Alsina T-Norm and T-Conorm and Their Applications in Group Decision-Making. Symmetry, 14(12), 2655. https://doi.org/10.3390/sym14122655

Senapati, T., Chen, G., Mesiar, R., & Yager, R. R. (2023). Intuitionistic fuzzy geometric aggregation operators in the framework of Aczel-Alsina triangular norms and their application to multiple attribute decision making. Expert Systems with Applications, 212, 118832. https://doi.org/10.1016/j.eswa.2022.118832

Ye, J., Du, S., & Yong, R. (2022). Aczel–Alsina Weighted Aggregation Operators of Neutrosophic Z-Numbers and Their Multiple Attribute Decision-Making Method. International Journal of Fuzzy Systems, 1-14. https://doi.org/10.1007/s40815-022-01289-w

Mahmood, T., Ali, Z., Baupradist, S., & Chinram, R. (2022). Complex Intuitionistic Fuzzy Aczel-Alsina Aggregation Operators and Their Application in Multi-Attribute Decision-Making. Symmetry, 14(11), 2255. https://doi.org/10.3390/sym14112255

Ashraf, S., Ahmad, S., Naeem, M., Riaz, M., & Alam, M. (2022). Novel EDAS methodology based on single-valued neutrosophic Aczel-Alsina aggregation information and their application in complex decision-making. Complexity, 2022. https://doi.org/10.1155/2022/2394472

Senapati, T., Simic, V., Saha, A., Dobrodolac, M., Rong, Y., & Tirkolaee, E. B. (2023). Intuitionistic fuzzy power Aczel-Alsina model for prioritization of sustainable transportation sharing practices. Engineering Applications of Artificial Intelligence, 119, 105716. https://doi.org/10.1016/j.engappai.2022.105716

Wang, H., Smarandache, F., Zhang, Y., & Sunderraman, R. (2010). Single valued neutrosophic sets. Infinite study, 12.

Ali, M., & Smarandache, F. (2017). Complex neutrosophic set. Neural computing and applications, 28, 1817-1834. https://doi.org/10.1007/s00521-015-2154-y

Published

2023-08-10

How to Cite

Naseem, A., Akram, M., Ullah, K., & Ali, Z. (2023). Aczel-Alsina Aggregation Operators Based on Complex Single-valued Neutrosophic Information and Their Application in Decision-Making Problems. Decision Making Advances, 1(1), 86–114. https://doi.org/10.31181/dma11202312