An Approach for Combining Linguistic and Numerical Information Based on the 2-Tuple Fuzzy Linguistic Representation Model in Decision-Making
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Implication
Methodological study demonstrates lossless integration of linguistic and numerical data using a 2-tuple fuzzy model, indicating enhanced precision in multi-attribute decision-making.
Key Points
- Develop a lossless method for combining numerical and linguistic information in multi-attribute decision-making using the 2-tuple fuzzy linguistic representation model.
- Derived mathematical conditions required for linguistic term sets to ensure lossless conversion between numerical and linguistic data.
- Utilized the 2-tuple fuzzy linguistic representation model as the foundational structure to unify qualitative and quantitative attributes.
- Implemented the resulting aggregation procedure within a multi-attribute decision-making framework dealing with mixed data types.
- Identified formal conditions on linguistic term sets that prevent information loss during transformations between numerical values and linguistic expressions.
- Demonstrated effective aggregation of heterogeneous data, enabling balanced multi-attribute evaluation across quantitative metrics and qualitative judgments.
Cite This Study
Herrera et al. (2000) studied this question.