Volume 23 • Issue 3 • PP: 140-147 • 2024
Selection of the best process for desalination under a Treesoft set environment using the multi-criteria decision-making method
Open Access & Copyright
© 2024 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
View PDF Abstract
Multi-criteria decision-making (MCDM), which has been called a revolution in the field, is one of the most exact methods for making decisions. Multicriteria decision-making (MCDM) is the process of selecting options by considering multiple criteria to determine which is best. A multitude of applications in engineering, design, and finance are possible with the tools and methods derived from MCDM. Application-oriented problems with multiple criteria involve ambiguous and more inaccurate options, to deal with this ambiguity Smarandache introduced Treesoft sets, which are an extension of hypersoft sets. So, in this paper, we will consider a real-life application-oriented problem “Desalination process” under the treesoft sets environment and find the best method for desalination using one of the MCDM methods.
Keywords
References
[1] Abbas, M, Murtaza.G & Smarandache,F. “Basic operations on hypersoft sets and hypersoft point”. Neutrosophic sets and systems, vol.35, no. 1, pp. 407-421 (2020).
[2] Atanassov, K. Intuitionistic fuzzy sets. “Fuzzy sets and systems”, vol. 20,0 no.1, pp. 87-96 (1986). http://dx.doi.org/10.1016/S0165-0114(86)80034-3
[3] Cagman, N., Enginoglu, S., & Citak,F. “Fuzzy soft set theory and its applications”, Iranian journal of fuzzy systems, vol.8, no.3, pp.137-147(2011). 10.22111/IJFS.2011.292
[4] Khalid Abd, Kazem Abhary, Romeo Marian. “Application of Fuzzy Logic to Multi-Objective Scheduling Problems in Robotic Flexible Assembly Cells”. Automation Control and Intelligent Systems. vol. 1, No. 3, 2013, pp. 34-41. 10.11648/j.acis.20130103.11
[5] Kong, Z., Wang., L., Wu, Z. “Application of fuzzy soft set in decision making problems based on grey theory” . J. Comput. Appl. Math.,vol. 236, pp. 1521-1530(2011). https://doi.org/10.1016/j.cam.2011.09.016
[6] Maji, P.K., Biswas, R., & Roy, A.R. “Fuzzy soft sets”. Journal of fuzzy mathematics. vol. 9, pp. 589-602 (2001).
[7] Maji, P.K, Biswas R and Roy A.R. “Soft set theory”, Computer. Math. Appl., vol. 45, pp. 555-562(2003). https://doi.org/10.1016/S0898-1221(03)00016-6
[8] Smarandache, F. ‘ Extension of soft sets to hypersoft set, and then to plithogenic hypersoft set, “ Neutrosophic Sets and system, vol. 22, pp. 168-170,(2018). 10.5281/zenodo.1408740
[9] Smarandache, F. “ Practical applications of IndetermSoft sets and IndetermHypersoft sets and Introduction to Treesoft set as an extension of Multisoft set, “ Neutrosophic Sets and System, vol.51, pp. 941-947, (2022). 10.5281/zenodo.7154238
[10] Smarandache, F. “New types of Soft sets, HyperSoft sets, IndetermSoft sets, IndetermHyperSoft set, and TreeSoft set”, Neutrosophic Sets and System, vol.8 (2023) https://doi.org/10.61356/j.nswa.2023.41.
[11] Yildiray Celik and Sultan Yamak, “Fuzzy soft set theory applied to medical diagnosis using fuzzy arithmetic operations” vol.1, no. 82 (2013). https://doi.org/10.1186/1029-242X-2013-82
[12] Zadeh L.A. “Fuzzy sets, Information and Control” vol. 8, pp. 338-353 (1965). https://doi.org/10.1016/S0019-9958(65)90241-X
Cite This Article
Choose your preferred format
Publisher's Note
The statements, opinions, and data presented in this article are solely those of the author(s) and do not necessarily represent those of ASPG, the journal, or its editors. ASPG and the editors disclaim responsibility for any harm arising from the use of any ideas, methods, instructions, or products described in this article, to the fullest extent permitted by applicable law.