Einstein Ordered Weighted Aggregation Operators for Pythagorean Fuzzy Hypersoft Set With Its Application to Solve MCDM Problem
The Pythagorean fuzzy hypersoft set is the most generalized form of the Pythagorean fuzzy soft set used to resolve indeterminate and inexplicit information in the decision-making procedure, considering the parameters’ multi-sub-attributes. Aggregation operators execute a dynamic role in c...
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9874804/ |
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| author | Rana Muhammad Zulqarnain Imran Siddique Rifaqat Ali Jan Awrejcewicz Hanen Karamti Dariusz Grzelczyk Aiyared Iampan Muhammad Asif |
| author_facet | Rana Muhammad Zulqarnain Imran Siddique Rifaqat Ali Jan Awrejcewicz Hanen Karamti Dariusz Grzelczyk Aiyared Iampan Muhammad Asif |
| author_sort | Rana Muhammad Zulqarnain |
| collection | DOAJ |
| description | The Pythagorean fuzzy hypersoft set is the most generalized form of the Pythagorean fuzzy soft set used to resolve indeterminate and inexplicit information in the decision-making procedure, considering the parameters’ multi-sub-attributes. Aggregation operators execute a dynamic role in considering the two prospect sequences and eliminating anxieties from this perception. The hybrid form of Pythagorean fuzzy sets with hypersoft sets has appeared as a supportive structure in fuzzy mathematics and ensued as a convenient perspective in decision-making. This paper prolongs the Einstein-weighted ordered aggregation operators for the Pythagorean fuzzy hypersoft set, which proficiently contracts with tentative and confusing data. Experts are using the Pythagorean fuzzy hypersoft set in their quest to report indefinite and specific decision-making processes. It is an effective technique for enlarging unsure facts in decision-making. Some operational laws for the Pythagorean fuzzy hypersoft set have been projected in light of Einstein’s operations. Two innovative Einstein-ordered aggregation operators were established based on operational laws: Pythagorean fuzzy hypersoft Einstein-ordered weighted average and Pythagorean fuzzy hypersoft Einstein-ordered weighted geometric operators with their essential properties. Multi-criteria decision-making is imperative in overcoming barriers to real-world complications. However, conventional methods of multi-criteria decision-making regularly provide inconsistent results. The extended model appraisals recognized score values to regulate robotic agri-farming equated to prevalent methods, which is more useful for agribusiness. A numerical illustration of decision-making complications in real-life farming is deliberated to authenticate the established method’s supremacy and applicability. Based on the anticipated aggregation operators, a robust multi-criteria decision-making method has been presented, which delivers the most appropriate outcomes compared to existing multi-criteria decision-making techniques. The consequences show that the intended approach is more effective and stable in handling rough information based on the Pythagorean fuzzy hypersoft set. |
| format | Article |
| id | doaj-art-b3dc97b5b1924f2ea019c9572e9fbbe3 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-b3dc97b5b1924f2ea019c9572e9fbbe32025-01-30T00:01:09ZengIEEEIEEE Access2169-35362022-01-0110952949532010.1109/ACCESS.2022.32037179874804Einstein Ordered Weighted Aggregation Operators for Pythagorean Fuzzy Hypersoft Set With Its Application to Solve MCDM ProblemRana Muhammad Zulqarnain0https://orcid.org/0000-0002-2656-8679Imran Siddique1Rifaqat Ali2Jan Awrejcewicz3https://orcid.org/0000-0003-0387-921XHanen Karamti4Dariusz Grzelczyk5Aiyared Iampan6https://orcid.org/0000-0002-0475-3320Muhammad Asif7https://orcid.org/0000-0001-5684-4737Department of Mathematics, Zhejiang Normal University, Jinhua, ChinaDepartment of Mathematics, University of Management and Technology, Lahore, PakistanDepartment of Mathematics, College of Science and Arts, Muhayil, King Khalid University, Abha, Saudi ArabiaDepartment of Automation, Biomechanics and Mechatronics, Lodz University of Technology, Lodz, PolandDepartment of Computer Sciences, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi ArabiaDepartment of Automation, Biomechanics and Mechatronics, Lodz University of Technology, Lodz, PolandDepartment of Mathematics, School of Science, University of Phayao, Mae Ka, Mueang, ThailandDepartment of Mathematics, University of Management and Technology Sialkot, Sialkot, PakistanThe Pythagorean fuzzy hypersoft set is the most generalized form of the Pythagorean fuzzy soft set used to resolve indeterminate and inexplicit information in the decision-making procedure, considering the parameters’ multi-sub-attributes. Aggregation operators execute a dynamic role in considering the two prospect sequences and eliminating anxieties from this perception. The hybrid form of Pythagorean fuzzy sets with hypersoft sets has appeared as a supportive structure in fuzzy mathematics and ensued as a convenient perspective in decision-making. This paper prolongs the Einstein-weighted ordered aggregation operators for the Pythagorean fuzzy hypersoft set, which proficiently contracts with tentative and confusing data. Experts are using the Pythagorean fuzzy hypersoft set in their quest to report indefinite and specific decision-making processes. It is an effective technique for enlarging unsure facts in decision-making. Some operational laws for the Pythagorean fuzzy hypersoft set have been projected in light of Einstein’s operations. Two innovative Einstein-ordered aggregation operators were established based on operational laws: Pythagorean fuzzy hypersoft Einstein-ordered weighted average and Pythagorean fuzzy hypersoft Einstein-ordered weighted geometric operators with their essential properties. Multi-criteria decision-making is imperative in overcoming barriers to real-world complications. However, conventional methods of multi-criteria decision-making regularly provide inconsistent results. The extended model appraisals recognized score values to regulate robotic agri-farming equated to prevalent methods, which is more useful for agribusiness. A numerical illustration of decision-making complications in real-life farming is deliberated to authenticate the established method’s supremacy and applicability. Based on the anticipated aggregation operators, a robust multi-criteria decision-making method has been presented, which delivers the most appropriate outcomes compared to existing multi-criteria decision-making techniques. The consequences show that the intended approach is more effective and stable in handling rough information based on the Pythagorean fuzzy hypersoft set.https://ieeexplore.ieee.org/document/9874804/Hypersoft setPythagorean fuzzy hypersoft setEinstein operatorsPythagorean fuzzy hypersoft Einstein-ordered weighted average operatorPythagorean fuzzy hypersoft Einstein ordered weighted geometric operatormulti-criteria decision making |
| spellingShingle | Rana Muhammad Zulqarnain Imran Siddique Rifaqat Ali Jan Awrejcewicz Hanen Karamti Dariusz Grzelczyk Aiyared Iampan Muhammad Asif Einstein Ordered Weighted Aggregation Operators for Pythagorean Fuzzy Hypersoft Set With Its Application to Solve MCDM Problem IEEE Access Hypersoft set Pythagorean fuzzy hypersoft set Einstein operators Pythagorean fuzzy hypersoft Einstein-ordered weighted average operator Pythagorean fuzzy hypersoft Einstein ordered weighted geometric operator multi-criteria decision making |
| title | Einstein Ordered Weighted Aggregation Operators for Pythagorean Fuzzy Hypersoft Set With Its Application to Solve MCDM Problem |
| title_full | Einstein Ordered Weighted Aggregation Operators for Pythagorean Fuzzy Hypersoft Set With Its Application to Solve MCDM Problem |
| title_fullStr | Einstein Ordered Weighted Aggregation Operators for Pythagorean Fuzzy Hypersoft Set With Its Application to Solve MCDM Problem |
| title_full_unstemmed | Einstein Ordered Weighted Aggregation Operators for Pythagorean Fuzzy Hypersoft Set With Its Application to Solve MCDM Problem |
| title_short | Einstein Ordered Weighted Aggregation Operators for Pythagorean Fuzzy Hypersoft Set With Its Application to Solve MCDM Problem |
| title_sort | einstein ordered weighted aggregation operators for pythagorean fuzzy hypersoft set with its application to solve mcdm problem |
| topic | Hypersoft set Pythagorean fuzzy hypersoft set Einstein operators Pythagorean fuzzy hypersoft Einstein-ordered weighted average operator Pythagorean fuzzy hypersoft Einstein ordered weighted geometric operator multi-criteria decision making |
| url | https://ieeexplore.ieee.org/document/9874804/ |
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