Linear diophantine multi-fuzzy aggregation operators and its application in digital transformation

Abstract

Digital transformation is the significant phenomena in contemporary global environment. All the conventional fuzzy sets are extended by the Linear Diophantine Fuzzy Set (LDFS). LDFS is the most viable adaptable method for dcision makers to choose their grade values as it includes reference parameters. The foremost vision is to promote the resilient integration of Linear Diophantine Multi-Fuzzy Set (LDMFS) as a model for constructing decisions in order to identify the appropriate standards for digital transformation. Aggregation Operators are crucial in fuzzy systems for fusing information. To aggregate the LDMF, a number of operators have been devised, such as the Linear Diophantine Multi-Fuzzy Weighted Geometric Operator (LDMFWGO), Linear Diophantine Multi-Fuzzy Ordered Weighted Geometric Operator (LDMFOWGO), Linear Diophantine Multi-Fuzzy Weighted Averaging Operator (LDMFWGO) and Linear Diophantine Multi-Fuzzy Ordered Weighted Averaging Operator (LDMFOWAO). By integrating preferred aggregating operations, a novel method for MCDM with LDMF data is studied. The best option from the current alternatives can be determined using these operators. Moreover, a comparison of LDMF operators is made. Additionally, the idea of a scoring function for LDF is designed to examine the rank of viable alternaties. Additionally, a novel approach to solving LDMF sets is suggested. The annals on organisational digital transformation is presented as the final section to test the supremacy of the theory. Accurate rankings for digital transformation are provided by the outcome. To exhibit the robustness of the MCDM methodology, a prompt comparative analysis is established between the suggested concept and the currently used approaches.

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“…Jeevitha et.al [24] discussed the problem of climate crisis by utilizing LDF DEMA-TEL approach. Subsequently, some enhancements of LDFS were addressed and discussed the application in the field of digital transformation [23], agri-drone [21], tender selection [22] medical diagnosis [45] Saeed et al used hybrid fuzzy hypersoft structures for optimization and efficient decisionmaking purposes [42]- [44].…”

Advancing Cybersecurity Strategies for Multinational Corporations: Novel Distance Measures in q-Rung Orthopair Multi-Fuzzy Systems

“…Inspired by these considerations, Pethaperumal et al [14] formulated the algebraic concepts of q-ROMFSs. Similarly, akin to a q-rung extension of multi-fuzzy set theory, Jeevitha et al [15] introduced the notion of LDMFSs. In recent times, this extension has found application in q-rung orthopair multi-fuzzy soft sets (q-ROMFS t S) [16] and linear Diophantine multi-fuzzy soft sets (LDMFS t S) [17].…”