Multi-Criteria Decision-Making Method Based on Weighted and Geometric Aggregate Operators of Linguistic Fuzzy-Valued Hypersoft Set with Application

Saqlain, M; Kumam, P; Kumam, W

Multi-Criteria Decision-Making Method Based on Weighted and Geometric Aggregate Operators of Linguistic Fuzzy-Valued Hypersoft Set with Application

Saqlain, M

Kumam, P Kumam, W

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Publication Type:: Journal Article
Citation:: Journal of Fuzzy Extension and Applications, 2025, 6, (2), pp. 344-370
Issue Date:: 2025-06-01

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Field	Value	Language
dc.contributor.author	Saqlain, M https://orcid.org/0000-0003-3617-6043
dc.contributor.author	Kumam, P
dc.contributor.author	Kumam, W
dc.date.accessioned	2026-02-04T02:51:05Z
dc.date.available	2026-02-04T02:51:05Z
dc.date.issued	2025-06-01
dc.identifier.citation	Journal of Fuzzy Extension and Applications, 2025, 6, (2), pp. 344-370
dc.identifier.issn	2783-1442
dc.identifier.issn	2717-3453
dc.identifier.uri	http://hdl.handle.net/10453/192967
dc.description.abstract	This study aims to fill the research gap and linguistic uncertainty associated with crypto mining. Recent environmental concerns such as increased carbon emissions have been raised due to cryptocurrency mining, and demand for energy production increases as cryptocurrency mining increases. The mathematical model can be used to evaluate and mitigate the environmental concerns associated with cryptocurrency mining activities. Thus, this paper presents the Linguistic Fuzzy-valued Hypersoft Set (LFHSs), its aggregate operators, and the unique mathematical technique for Multi-Criteria Decision-Making (MCDM) method based on proposed aggregation to evaluate the uncertainty and vagueness associated with crypto mining and its impacts on the environment. This analyzes the comprehensive understanding of environmental problems such as increased carbon emissions, higher demand for electricity associated with crypto mining, and the inherent uncertainty associated with data processing in the Decision-Making (DM) process using LFHSs. Linguistic terms are used to collect and express complicated, ambiguous, and amorphous information. The modeling and construction of the problem involve the identification of energy production as alternatives, and relevant environmental factors are in the form of further bifurcation as attributes. Subsequently, the fuzzy values are assigned to each linguistic attribute by considering individual impact. This allows for a more accurate representation of the many factors of the environmental effect of crypto mining. The proposed MCDM method, based on weighted and geometric aggregate operators, solves the case study. The results evaluated are then compared with the existing studies, and it shows that the study has the potential to assist researchers, industry stakeholders, and policymakers in creating strategies that will effectively address the environmental problems raised by crypto mining while minimizing energy use and promoting sustainable practices in changing digital environment.
dc.language	en
dc.relation.ispartof	Journal of Fuzzy Extension and Applications
dc.relation.isbasedon	10.22105/jfea.2024.475488.1609
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Multi-Criteria Decision-Making Method Based on Weighted and Geometric Aggregate Operators of Linguistic Fuzzy-Valued Hypersoft Set with Application
dc.type	Journal Article
utslib.citation.volume	6
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	open_access	*
dc.rights.license	This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/
dc.date.updated	2026-02-04T02:51:04Z
pubs.issue	2
pubs.publication-status	Published
pubs.volume	6
utslib.citation.issue	2

Abstract:

This study aims to fill the research gap and linguistic uncertainty associated with crypto mining. Recent environmental concerns such as increased carbon emissions have been raised due to cryptocurrency mining, and demand for energy production increases as cryptocurrency mining increases. The mathematical model can be used to evaluate and mitigate the environmental concerns associated with cryptocurrency mining activities. Thus, this paper presents the Linguistic Fuzzy-valued Hypersoft Set (LFHSs), its aggregate operators, and the unique mathematical technique for Multi-Criteria Decision-Making (MCDM) method based on proposed aggregation to evaluate the uncertainty and vagueness associated with crypto mining and its impacts on the environment. This analyzes the comprehensive understanding of environmental problems such as increased carbon emissions, higher demand for electricity associated with crypto mining, and the inherent uncertainty associated with data processing in the Decision-Making (DM) process using LFHSs. Linguistic terms are used to collect and express complicated, ambiguous, and amorphous information. The modeling and construction of the problem involve the identification of energy production as alternatives, and relevant environmental factors are in the form of further bifurcation as attributes. Subsequently, the fuzzy values are assigned to each linguistic attribute by considering individual impact. This allows for a more accurate representation of the many factors of the environmental effect of crypto mining. The proposed MCDM method, based on weighted and geometric aggregate operators, solves the case study. The results evaluated are then compared with the existing studies, and it shows that the study has the potential to assist researchers, industry stakeholders, and policymakers in creating strategies that will effectively address the environmental problems raised by crypto mining while minimizing energy use and promoting sustainable practices in changing digital environment.

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http://hdl.handle.net/10453/192967