Einstein Aggregation Operator Technique for Linguistic q-Rung Orthopair Fuzzy Hypersoft Set With Application to Sustainable Construction Industry
The unclear and vague information, subjective assessments, and the languages spoken with diversity in these domains are some of the linguistic features that complicate the decision-making process in the construction industry. Language-specific terminology, context-specific terms, and terms requiring...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10942349/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849699858703712256 |
|---|---|
| author | Muhammad Saqlain Harish Garg Wiyada Kumam Rana Muhammad Zulqarnain |
| author_facet | Muhammad Saqlain Harish Garg Wiyada Kumam Rana Muhammad Zulqarnain |
| author_sort | Muhammad Saqlain |
| collection | DOAJ |
| description | The unclear and vague information, subjective assessments, and the languages spoken with diversity in these domains are some of the linguistic features that complicate the decision-making process in the construction industry. Language-specific terminology, context-specific terms, and terms requiring a common translation all provide challenges. Furthermore, it is challenging to compile linguistic information from several sources with a cohesive framework due to interpretation variability. To address these challenges, in this article, we propose a novel theory term as linguistic q-rung orthopair fuzzy hypersoft set (Lq-ROFHS). To aggregate the various information, we defined some new weighted averaging and geometric operators by using Einstein t-norm operations. The fundamental properties of all these stated operators are derived in detail. To illustrate the method, a multi-criteria group decision making algorithm is proposed by using the stated operators and apply them to the case study related to the selection of the best construction company. To demonstrate the efficiency of the proposed algorithm, a comparative analysis between the proposed and the several existing studies is done by comparing the order of preference. The proposed approach is a significant advancement that will enable decision-makers to navigate the complexities of their choice with greater assurance and precision using a single tool. |
| format | Article |
| id | doaj-art-603e820df6c846e281d24ecc65512c19 |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-603e820df6c846e281d24ecc65512c192025-08-20T03:18:27ZengIEEEIEEE Access2169-35362025-01-0113630296304710.1109/ACCESS.2025.355501510942349Einstein Aggregation Operator Technique for Linguistic q-Rung Orthopair Fuzzy Hypersoft Set With Application to Sustainable Construction IndustryMuhammad Saqlain0https://orcid.org/0000-0003-3617-6043Harish Garg1https://orcid.org/0000-0001-9099-8422Wiyada Kumam2https://orcid.org/0000-0001-8773-4821Rana Muhammad Zulqarnain3https://orcid.org/0000-0002-2656-8679Department of Mathematics, Faculty of Science, King Mongkut’s University of Technology Thonburi, Bangkok, ThailandDepartment of Mathematics, >Thapar Institute of Engineering and Technology (Deemed University), Patiala, Punjab, IndiaDepartment of Mathematics and Computer Science, Faculty of Science and Technology, Applied Mathematics for Science and Engineering Research Unit (AMSERU) Program in Applied Statistics, Rajamangala University of Technology Thanyaburi, Klong Luang, Pathum Thani, ThailandDepartment of Mathematics, Saveetha School of Engineering, SIMATS Thandalam, Chennai, Tamil Nadu, IndiaThe unclear and vague information, subjective assessments, and the languages spoken with diversity in these domains are some of the linguistic features that complicate the decision-making process in the construction industry. Language-specific terminology, context-specific terms, and terms requiring a common translation all provide challenges. Furthermore, it is challenging to compile linguistic information from several sources with a cohesive framework due to interpretation variability. To address these challenges, in this article, we propose a novel theory term as linguistic q-rung orthopair fuzzy hypersoft set (Lq-ROFHS). To aggregate the various information, we defined some new weighted averaging and geometric operators by using Einstein t-norm operations. The fundamental properties of all these stated operators are derived in detail. To illustrate the method, a multi-criteria group decision making algorithm is proposed by using the stated operators and apply them to the case study related to the selection of the best construction company. To demonstrate the efficiency of the proposed algorithm, a comparative analysis between the proposed and the several existing studies is done by comparing the order of preference. The proposed approach is a significant advancement that will enable decision-makers to navigate the complexities of their choice with greater assurance and precision using a single tool.https://ieeexplore.ieee.org/document/10942349/Aggregate operatordecision makingeinstein operatorfuzzy sethypersoft setlinguistic quantifiers |
| spellingShingle | Muhammad Saqlain Harish Garg Wiyada Kumam Rana Muhammad Zulqarnain Einstein Aggregation Operator Technique for Linguistic q-Rung Orthopair Fuzzy Hypersoft Set With Application to Sustainable Construction Industry IEEE Access Aggregate operator decision making einstein operator fuzzy set hypersoft set linguistic quantifiers |
| title | Einstein Aggregation Operator Technique for Linguistic q-Rung Orthopair Fuzzy Hypersoft Set With Application to Sustainable Construction Industry |
| title_full | Einstein Aggregation Operator Technique for Linguistic q-Rung Orthopair Fuzzy Hypersoft Set With Application to Sustainable Construction Industry |
| title_fullStr | Einstein Aggregation Operator Technique for Linguistic q-Rung Orthopair Fuzzy Hypersoft Set With Application to Sustainable Construction Industry |
| title_full_unstemmed | Einstein Aggregation Operator Technique for Linguistic q-Rung Orthopair Fuzzy Hypersoft Set With Application to Sustainable Construction Industry |
| title_short | Einstein Aggregation Operator Technique for Linguistic q-Rung Orthopair Fuzzy Hypersoft Set With Application to Sustainable Construction Industry |
| title_sort | einstein aggregation operator technique for linguistic q rung orthopair fuzzy hypersoft set with application to sustainable construction industry |
| topic | Aggregate operator decision making einstein operator fuzzy set hypersoft set linguistic quantifiers |
| url | https://ieeexplore.ieee.org/document/10942349/ |
| work_keys_str_mv | AT muhammadsaqlain einsteinaggregationoperatortechniqueforlinguisticqrungorthopairfuzzyhypersoftsetwithapplicationtosustainableconstructionindustry AT harishgarg einsteinaggregationoperatortechniqueforlinguisticqrungorthopairfuzzyhypersoftsetwithapplicationtosustainableconstructionindustry AT wiyadakumam einsteinaggregationoperatortechniqueforlinguisticqrungorthopairfuzzyhypersoftsetwithapplicationtosustainableconstructionindustry AT ranamuhammadzulqarnain einsteinaggregationoperatortechniqueforlinguisticqrungorthopairfuzzyhypersoftsetwithapplicationtosustainableconstructionindustry |