Hesitant Fuzzy Linguistic Group Decision-Making Techniques
Summary
Hesitant fuzzy linguistic group decision-making techniques address situations in which experts or stakeholders hesitate among several linguistic expressions—such as “low,” “medium” or “high”—to evaluate alternatives under uncertainty. By allowing a set of possible linguistic values rather than forcing a single label, these methods capture the cognitive ambiguity inherent in human assessment. Core developments include the formal definition of hesitant fuzzy linguistic term sets, the design of aggregation operators to combine multiple experts’ evaluations, and the introduction of distance and similarity measures to compare alternatives. Weighting schemes—from entropy-based approaches to intercriteria correlation analyses—have been adapted to the hesitant fuzzy context, and various multi-criteria decision-making (MCDM) methods (for example TOPSIS, EDAS and TODIM) have been extended to operate on these enriched linguistic structures. Applications span credit-risk assessment, supplier selection, environmental planning and technology investment, demonstrating global relevance in finance, logistics and sustainable management. The field continues to evolve through the integration of behavioural considerations, refined score functions and enhanced mathematical properties that preserve fidelity to original expert judgements.
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Hesitant Fuzzy Linguistic Group Decision-Making Techniques publication trend
The graph below shows the total number of articles in hesitant fuzzy linguistic group decision-making techniques across all publications each year (not limited to Nature Index journals).
Technical terms
Hesitant fuzzy linguistic term set (HFLTS): A collection of possible linguistic labels representing an expert’s hesitation among terms when assessing an alternative.
Aggregation operator: A mathematical function that combines multiple hesitant fuzzy linguistic evaluations into a single collective judgement.
Distance measure: A metric for quantifying the difference or similarity between two hesitant fuzzy linguistic assessments.
Entropy weight: An objective weighting method based on information entropy, adapted to determine criterion importance in hesitant fuzzy environments.
MCDM (Multi-Criteria Decision-Making): A framework for ranking or selecting alternatives based on multiple, often conflicting, criteria under uncertainty.
References
- Connecting the Numerical Scale Model With Assessing Attitudes and its Application to Hesitant Fuzzy Linguistic Multi-attribute Decision Making. Journal of Operations Intelligence (2024).
- Prioritizing real estate enterprises based on credit risk assessment: an integrated multi-criteria group decision support framework. Financial Innovation (2023).
- Linguistic Pythagorean fuzzy CRITIC-EDAS method for multiple-attribute group decision analysis. Engineering Applications of Artificial Intelligence (2023).
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