Generalized Inverse of Quadri-Partitioned Neutrosophic Fuzzy Matrices and its Application to Decision-Making Problems
This paper presents a novel framework for computing the generalized inverse (g-inverse) and the Moore-Penrose inverse of Quadri-Partitioned Neutrosophic Fuzzy Matrices (QPNFMs). To the best of our knowledge, no existing algorithm addresses the computation of the g-inverse for QPNFMs. In this study,...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
University of New Mexico
2025-07-01
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| Series: | Neutrosophic Sets and Systems |
| Subjects: | |
| Online Access: | https://fs.unm.edu/NSS/36QuadriPartitioned.pdf |
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| Summary: | This paper presents a novel framework for computing the generalized inverse (g-inverse) and the Moore-Penrose inverse of Quadri-Partitioned Neutrosophic Fuzzy Matrices (QPNFMs). To the best of our knowledge, no existing algorithm addresses the computation of the g-inverse for QPNFMs. In this study, we establish necessary and sufficient conditions for the existence of the g-inverse and develop an efficient algorithm for its computation. Furthermore, we explore several fundamental properties and theoretical results related to the g-inverse of QPNFMs, including uniqueness conditions and algebraic structures. In addition to theoretical advancements, we introduce a novel decision-making algorithm leveraging QPNFMs and their g-inverse. This algorithm enhances decision analysis in complex and uncertain environments by effectively handling indeterminate and inconsistent information. An illustrative example is provided to demonstrate the practical applicability and computational efficiency of the proposed approach. The results validate the accuracy of the g-inverse computation and highlight the utility of QPNFMs in decision-making scenarios. Our findings offer a significant contribution to both matrix theory and neutrosophic logic-based decision analysis, opening new avenues for future research in uncertainty modeling and computational intelligence. |
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| ISSN: | 2331-6055 2331-608X |