Scrutiny of Neutrosophic Cubic Fuzzy Data with Different Parametric Values using Bonferroni Weighted Mean: A Robust MCDM Approach

Adil Darvesh; Khalid Naeem; Syed Bilal Hussain Shah

doi:10.31181/dma31202576

Authors

Adil Darvesh Department of Mathematics and Statistics, Hazara University, Mansehra, 21300, Pakistan https://orcid.org/0000-0003-4906-3072
Khalid Naeem Department of Mathematics, Federal Govt. Degree College, Aziz Bhatti Road, Lahore Cantt., Pakistan https://orcid.org/0000-0003-4614-5689
Syed Bilal Hussain Shah Department of Mathematics and Statistics, Hazara University, Mansehra, 21300, Pakistan https://orcid.org/0009-0008-3825-933X

DOI:

https://doi.org/10.31181/dma31202576

Keywords:

Neutrosophic Cubic Fuzzy Sets, Bonferroni Mean, Aggregating Operator, Multiple-Criteria Decision-Making

Abstract

Neutrosophic cubic interval-valued fuzzy data-based aggregation operators are critical tools for addressing the intricacy of modern decision-making problems. They can handle diverse forms of fuzziness, uncertainty, and indeterminacy, which makes them able to tackle problems like product selection, resource allocation, and project prioritization. Taking the full support of Bonferroni mean, the current approach focuses on two novel aggregation operators such as Neutrosophic cubic fuzzy arithmetic Bonferroni mean NCFABM^(x,y) and weighted Neutrosophic cubic fuzzy arithmetic Bonferroni mean WNCFABM^(x,y). In addition, parametric value is also incorporated, which could lead to presenting a summative assessment in diverse scenarios. Furthermore, proposed aggregation operators are employed in multiple-criteria decision-making environments to solve numerical examples based on real-life problems; i.e. usefulness of the suggested aggregation operators in the system for managing health care. Finally, in support of our provided work, a detailed comparison analysis based on the suggested scheme versus current schemes based on self-defeating scenarios has been added to demonstrate reliability and validity.

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