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Granular Computing
Published in: Granular Computing 3/2023

23-09-2022 | Original Paper

Multi-attribute group decision-making based on probabilistic dual hesitant fuzzy Maclaurin symmetric mean operators

Authors: Qasim Noor, Tabasam Rashid, Ismat Beg

Published in: Granular Computing | Issue 3/2023

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Abstract

In this study, we put forward the dual Maclaurin symmetric mean (DMSM) and the Maclaurin symmetric mean (MSM) operators with the context of the probabilistic dual hesitant fuzzy set (PDHFS), which can address the issues in previous probabilistic dual hesitant fuzzy aggregation operators. Some novel operators based on MSM and DMSM for aggregating PDHF information are prepared, followed by several properties and special cases. Namely, the PDHFMSM, weighted PDHFMSM (WPDHFMSM), PDHFDMSM, weighted PDHFDMSM (WPDHFDMSM) operators. Furthermore, some necessary characteristics and exceptional cases concerning different parametric values of these operators are discussed. Additionally, two new methods based on the WPDHFMSM and WPDHFDMSM operators have been developed with the help of COPRAS technique to deal with multi-attribute group decision-making problems. Lastly, the validity and effectiveness of the intended methods are demonstrated through a case study on selecting the best photovoltaic cells.
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Metadata
Title
Multi-attribute group decision-making based on probabilistic dual hesitant fuzzy Maclaurin symmetric mean operators
Authors
Qasim Noor
Tabasam Rashid
Ismat Beg
Publication date
23-09-2022
Publisher
Springer International Publishing
Published in
Granular Computing / Issue 3/2023
Print ISSN: 2364-4966
Electronic ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-022-00346-x

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