An extended TOPSIS technique based on correlation coefficient for interval-valued q-rung orthopair fuzzy hypersoft set in multi-attribute group decision-making
Abstract The accurate determination of results in decision analysis is usually predicated on the association between two factors. Although generating data for analytical purposes presents an apparent hurdle, the data obtained may present hurdles in its interpretation. Correlation coefficients can be...
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| Format: | Article |
| Language: | English |
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Springer
2025-04-01
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| Series: | Complex & Intelligent Systems |
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| Online Access: | https://doi.org/10.1007/s40747-025-01838-4 |
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| author | Rana Muhammad Zulqarnain Imran Siddique Sameh Askar Ahmad M. Alshamrani Dragan Pamucar Vladimir Simic |
| author_facet | Rana Muhammad Zulqarnain Imran Siddique Sameh Askar Ahmad M. Alshamrani Dragan Pamucar Vladimir Simic |
| author_sort | Rana Muhammad Zulqarnain |
| collection | DOAJ |
| description | Abstract The accurate determination of results in decision analysis is usually predicated on the association between two factors. Although generating data for analytical purposes presents an apparent hurdle, the data obtained may present hurdles in its interpretation. Correlation coefficients can be used to analyze the interaction between two factors and their variations. These coefficients deliver an objective description of the association between parameters, assisting in predicting and assessing alterations between particular parameters. The purpose of this research is to explore the applicability of correlation coefficients (CC) and weighted correlation coefficients (WCC) in interval-valued q-rung orthopair fuzzy hypersoft sets (IVq-ROFHSS) structures with their essential characteristics. These measures are developed to address the inevitable confusion, inconsistency, and volatility in real-life decision-making challenges. The implementation of these components attempts to boost the productivity of the technique for order preference by similarity to the ideal solution (TOPSIS) method. The computational models with correlation constraints are presented to determine the reliability and regularity of the proposed method. This research proves that the proposed technique is effective for multi-attribute group decision-making (MAGDM), particularly for analyzing and prioritizing convoluted data sets. Moreover, a numerical illustration is presented to clarify how the advocated decision-making methodology can be implemented in reality in evaluating bio-medical disposal techniques for hospitals. This study determines incineration as the most beneficial method for BMW disposal, demonstrating its more efficient use of alternative disposal techniques. A comparative analysis further substantiates the feasibility and effectiveness of the proposed approach over other decision-making techniques. |
| format | Article |
| id | doaj-art-c6eeeabc7b714bdf921c90346f66c869 |
| institution | DOAJ |
| issn | 2199-4536 2198-6053 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Springer |
| record_format | Article |
| series | Complex & Intelligent Systems |
| spelling | doaj-art-c6eeeabc7b714bdf921c90346f66c8692025-08-20T03:07:55ZengSpringerComplex & Intelligent Systems2199-45362198-60532025-04-0111613410.1007/s40747-025-01838-4An extended TOPSIS technique based on correlation coefficient for interval-valued q-rung orthopair fuzzy hypersoft set in multi-attribute group decision-makingRana Muhammad Zulqarnain0Imran Siddique1Sameh Askar2Ahmad M. Alshamrani3Dragan Pamucar4Vladimir Simic5School of Economics and Management, Tongji UniversityDepartment of Mathematics, University of SargodhaDepartment of Statistics and Operations Research, College of Science, King Saud UniversityDepartment of Statistics and Operations Research, College of Science, King Saud UniversityDepartment of Operations Research and Statistics, Faculty of Organizational Sciences, University of BelgradeFaculty of Transport and Traffic Engineering, University of BelgradeAbstract The accurate determination of results in decision analysis is usually predicated on the association between two factors. Although generating data for analytical purposes presents an apparent hurdle, the data obtained may present hurdles in its interpretation. Correlation coefficients can be used to analyze the interaction between two factors and their variations. These coefficients deliver an objective description of the association between parameters, assisting in predicting and assessing alterations between particular parameters. The purpose of this research is to explore the applicability of correlation coefficients (CC) and weighted correlation coefficients (WCC) in interval-valued q-rung orthopair fuzzy hypersoft sets (IVq-ROFHSS) structures with their essential characteristics. These measures are developed to address the inevitable confusion, inconsistency, and volatility in real-life decision-making challenges. The implementation of these components attempts to boost the productivity of the technique for order preference by similarity to the ideal solution (TOPSIS) method. The computational models with correlation constraints are presented to determine the reliability and regularity of the proposed method. This research proves that the proposed technique is effective for multi-attribute group decision-making (MAGDM), particularly for analyzing and prioritizing convoluted data sets. Moreover, a numerical illustration is presented to clarify how the advocated decision-making methodology can be implemented in reality in evaluating bio-medical disposal techniques for hospitals. This study determines incineration as the most beneficial method for BMW disposal, demonstrating its more efficient use of alternative disposal techniques. A comparative analysis further substantiates the feasibility and effectiveness of the proposed approach over other decision-making techniques.https://doi.org/10.1007/s40747-025-01838-4Interval-valued q-rung orthopair fuzzy hypersoft setCorrelation coefficientWeighted correlation coefficientTOPSISMAGDMBMW |
| spellingShingle | Rana Muhammad Zulqarnain Imran Siddique Sameh Askar Ahmad M. Alshamrani Dragan Pamucar Vladimir Simic An extended TOPSIS technique based on correlation coefficient for interval-valued q-rung orthopair fuzzy hypersoft set in multi-attribute group decision-making Complex & Intelligent Systems Interval-valued q-rung orthopair fuzzy hypersoft set Correlation coefficient Weighted correlation coefficient TOPSIS MAGDM BMW |
| title | An extended TOPSIS technique based on correlation coefficient for interval-valued q-rung orthopair fuzzy hypersoft set in multi-attribute group decision-making |
| title_full | An extended TOPSIS technique based on correlation coefficient for interval-valued q-rung orthopair fuzzy hypersoft set in multi-attribute group decision-making |
| title_fullStr | An extended TOPSIS technique based on correlation coefficient for interval-valued q-rung orthopair fuzzy hypersoft set in multi-attribute group decision-making |
| title_full_unstemmed | An extended TOPSIS technique based on correlation coefficient for interval-valued q-rung orthopair fuzzy hypersoft set in multi-attribute group decision-making |
| title_short | An extended TOPSIS technique based on correlation coefficient for interval-valued q-rung orthopair fuzzy hypersoft set in multi-attribute group decision-making |
| title_sort | extended topsis technique based on correlation coefficient for interval valued q rung orthopair fuzzy hypersoft set in multi attribute group decision making |
| topic | Interval-valued q-rung orthopair fuzzy hypersoft set Correlation coefficient Weighted correlation coefficient TOPSIS MAGDM BMW |
| url | https://doi.org/10.1007/s40747-025-01838-4 |
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