Partitioned Maclaurin symmetric mean operators in bipolar complex fuzzy sets for multiattribute decision making

Abstract Mathematical tools are crucial for dealing with uncertainty because they provide a rigorous and logical framework for evaluating, measuring, and making decisions in the presence of ambiguous information. The bipolar complex fuzzy is one of the mathematical methods for simultaneously handlin...

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Main Authors: Ubaid ur Rehman, Ibrahim Aldayel, Meraj Ali Khan, Tahir Mahmood
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-93452-0
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author Ubaid ur Rehman
Ibrahim Aldayel
Meraj Ali Khan
Tahir Mahmood
author_facet Ubaid ur Rehman
Ibrahim Aldayel
Meraj Ali Khan
Tahir Mahmood
author_sort Ubaid ur Rehman
collection DOAJ
description Abstract Mathematical tools are crucial for dealing with uncertainty because they provide a rigorous and logical framework for evaluating, measuring, and making decisions in the presence of ambiguous information. The bipolar complex fuzzy is one of the mathematical methods for simultaneously handling dual aspect and second-dimensional information. Thus, in this script, we propound aggregation operators “partitioned Maclaurin symmetric mean and partitioned dual Maclaurin symmetric mean” within bipolar complex fuzzy set that is bipolar complex fuzzy partitioned Maclaurin symmetric mean and bipolar complex fuzzy partitioned dual Maclaurin symmetric mean, bipolar complex fuzzy weighted partitioned Maclaurin symmetric mean and bipolar complex fuzzy weighted partitioned dual Maclaurin symmetric mean operators. We also propound the related axioms of the invented operators. By employing the deduced aggregation operators, we produce a technique of multiattribute decision making within bipolar complex fuzzy sets to overcome awkward uncertainties. After that, we demonstrate an explanatory example for revealing the significance and practicability of the deduced theory and then we analyze the reliability and legitimacy of the propounded operators by comparing them with some prevailing work.
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spelling doaj-art-cfaf365fc59d4e3a8420a6e3d8ff99502025-08-20T03:14:06ZengNature PortfolioScientific Reports2045-23222025-04-0115111810.1038/s41598-025-93452-0Partitioned Maclaurin symmetric mean operators in bipolar complex fuzzy sets for multiattribute decision makingUbaid ur Rehman0Ibrahim Aldayel1Meraj Ali Khan2Tahir Mahmood3Department of Mathematics, University of Management and TechnologyDepartment of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU)Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU)Department of Mathematics and Statistics, International Islamic University IslamabadAbstract Mathematical tools are crucial for dealing with uncertainty because they provide a rigorous and logical framework for evaluating, measuring, and making decisions in the presence of ambiguous information. The bipolar complex fuzzy is one of the mathematical methods for simultaneously handling dual aspect and second-dimensional information. Thus, in this script, we propound aggregation operators “partitioned Maclaurin symmetric mean and partitioned dual Maclaurin symmetric mean” within bipolar complex fuzzy set that is bipolar complex fuzzy partitioned Maclaurin symmetric mean and bipolar complex fuzzy partitioned dual Maclaurin symmetric mean, bipolar complex fuzzy weighted partitioned Maclaurin symmetric mean and bipolar complex fuzzy weighted partitioned dual Maclaurin symmetric mean operators. We also propound the related axioms of the invented operators. By employing the deduced aggregation operators, we produce a technique of multiattribute decision making within bipolar complex fuzzy sets to overcome awkward uncertainties. After that, we demonstrate an explanatory example for revealing the significance and practicability of the deduced theory and then we analyze the reliability and legitimacy of the propounded operators by comparing them with some prevailing work.https://doi.org/10.1038/s41598-025-93452-0Bipolar complex fuzzy setsPartition Maclaurin/partition dual Maclaurin mean operatorsDecision making technique
spellingShingle Ubaid ur Rehman
Ibrahim Aldayel
Meraj Ali Khan
Tahir Mahmood
Partitioned Maclaurin symmetric mean operators in bipolar complex fuzzy sets for multiattribute decision making
Scientific Reports
Bipolar complex fuzzy sets
Partition Maclaurin/partition dual Maclaurin mean operators
Decision making technique
title Partitioned Maclaurin symmetric mean operators in bipolar complex fuzzy sets for multiattribute decision making
title_full Partitioned Maclaurin symmetric mean operators in bipolar complex fuzzy sets for multiattribute decision making
title_fullStr Partitioned Maclaurin symmetric mean operators in bipolar complex fuzzy sets for multiattribute decision making
title_full_unstemmed Partitioned Maclaurin symmetric mean operators in bipolar complex fuzzy sets for multiattribute decision making
title_short Partitioned Maclaurin symmetric mean operators in bipolar complex fuzzy sets for multiattribute decision making
title_sort partitioned maclaurin symmetric mean operators in bipolar complex fuzzy sets for multiattribute decision making
topic Bipolar complex fuzzy sets
Partition Maclaurin/partition dual Maclaurin mean operators
Decision making technique
url https://doi.org/10.1038/s41598-025-93452-0
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