T-spherical fuzzy information aggregation with multi-criteria decision-making
T-spherical fuzzy sets (T-SPFSs) have gained popularity because of their ability to account for uncertainty more effectively and spanning a larger domain. The sum of the t-th power of membership grades in T-SPFSs is close to a unit interval, allowing for greater uncertainty. As a result, this set ou...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2023-02-01
|
| Series: | AIMS Mathematics |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/math.2023512?viewType=HTML |
| _version_ | 1811157968309190656 |
|---|---|
| author | Hafiz Muhammad Athar Farid Muhammad Riaz Gustavo Santos Garcia |
| author_facet | Hafiz Muhammad Athar Farid Muhammad Riaz Gustavo Santos Garcia |
| author_sort | Hafiz Muhammad Athar Farid |
| collection | DOAJ |
| description | T-spherical fuzzy sets (T-SPFSs) have gained popularity because of their ability to account for uncertainty more effectively and spanning a larger domain. The sum of the t-th power of membership grades in T-SPFSs is close to a unit interval, allowing for greater uncertainty. As a result, this set outperforms traditional fuzzy structures. The "multi-criteria decision-making" (MCDM) approach is a widely used technique that requires the use of some aggregation tools, and various such aggregation operators (AOs) have been developed over the years to achieve this purpose. The purpose of this paper is to propose some new operational laws and AOs for use in a T-spherical fuzzy environment. In this regard, we presented some new neutral or fair operational rules that combine the concept of proportional distribution to provide a neutral or fair solution to the membership, abstinence, and non-membership of T-spherical fuzzy numbers (T-SPFNs). Based on the obtained operational rules, we presented the "T-spherical fuzzy fairly weighted average operator" and the "T-spherical fuzzy fairly ordered weighted averaging operator". Compared to earlier methodologies, the proposed AOs provide more generalised, reliable, and accurate information. In addition, under T-SPFSs, an MCDM approach is developed employing suggested AOs with several decision-makers (DMs) and partial weight details. Finally, to demonstrate the applicability of the innovative technique, we give an actual case study of "food waste treatment technology" (FWTT) selection under T-SPFSs scenarios. A comparison with an existing model has also been undertaken to confirm the validity and robustness of the acquired results. |
| first_indexed | 2024-04-10T05:16:29Z |
| format | Article |
| id | doaj.art-eaebc17eb9c5441db0624a5ca6dde889 |
| institution | Directory Open Access Journal |
| issn | 2473-6988 |
| language | English |
| last_indexed | 2024-04-10T05:16:29Z |
| publishDate | 2023-02-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Mathematics |
| spelling | doaj.art-eaebc17eb9c5441db0624a5ca6dde8892023-03-09T01:26:56ZengAIMS PressAIMS Mathematics2473-69882023-02-0185101131014510.3934/math.2023512T-spherical fuzzy information aggregation with multi-criteria decision-makingHafiz Muhammad Athar Farid0Muhammad Riaz1Gustavo Santos Garcia21. Department of Mathematics, University of the Punjab, Lahore, Pakistan1. Department of Mathematics, University of the Punjab, Lahore, Pakistan2. Department of Economics and Economic History, University of Salamanca, Salamanca, SpainT-spherical fuzzy sets (T-SPFSs) have gained popularity because of their ability to account for uncertainty more effectively and spanning a larger domain. The sum of the t-th power of membership grades in T-SPFSs is close to a unit interval, allowing for greater uncertainty. As a result, this set outperforms traditional fuzzy structures. The "multi-criteria decision-making" (MCDM) approach is a widely used technique that requires the use of some aggregation tools, and various such aggregation operators (AOs) have been developed over the years to achieve this purpose. The purpose of this paper is to propose some new operational laws and AOs for use in a T-spherical fuzzy environment. In this regard, we presented some new neutral or fair operational rules that combine the concept of proportional distribution to provide a neutral or fair solution to the membership, abstinence, and non-membership of T-spherical fuzzy numbers (T-SPFNs). Based on the obtained operational rules, we presented the "T-spherical fuzzy fairly weighted average operator" and the "T-spherical fuzzy fairly ordered weighted averaging operator". Compared to earlier methodologies, the proposed AOs provide more generalised, reliable, and accurate information. In addition, under T-SPFSs, an MCDM approach is developed employing suggested AOs with several decision-makers (DMs) and partial weight details. Finally, to demonstrate the applicability of the innovative technique, we give an actual case study of "food waste treatment technology" (FWTT) selection under T-SPFSs scenarios. A comparison with an existing model has also been undertaken to confirm the validity and robustness of the acquired results.https://www.aimspress.com/article/doi/10.3934/math.2023512?viewType=HTMLfairly operationst-spherical fuzzy numbersaggregation operatorsoptimization model |
| spellingShingle | Hafiz Muhammad Athar Farid Muhammad Riaz Gustavo Santos Garcia T-spherical fuzzy information aggregation with multi-criteria decision-making AIMS Mathematics fairly operations t-spherical fuzzy numbers aggregation operators optimization model |
| title | T-spherical fuzzy information aggregation with multi-criteria decision-making |
| title_full | T-spherical fuzzy information aggregation with multi-criteria decision-making |
| title_fullStr | T-spherical fuzzy information aggregation with multi-criteria decision-making |
| title_full_unstemmed | T-spherical fuzzy information aggregation with multi-criteria decision-making |
| title_short | T-spherical fuzzy information aggregation with multi-criteria decision-making |
| title_sort | t spherical fuzzy information aggregation with multi criteria decision making |
| topic | fairly operations t-spherical fuzzy numbers aggregation operators optimization model |
| url | https://www.aimspress.com/article/doi/10.3934/math.2023512?viewType=HTML |
| work_keys_str_mv | AT hafizmuhammadatharfarid tsphericalfuzzyinformationaggregationwithmulticriteriadecisionmaking AT muhammadriaz tsphericalfuzzyinformationaggregationwithmulticriteriadecisionmaking AT gustavosantosgarcia tsphericalfuzzyinformationaggregationwithmulticriteriadecisionmaking |