MCDMRankingHesitant fuzzy linguistic
Hesitant Fuzzy Linguistic Projection-Based MABAC with Bonferroni Mean (Sun et al. 2018)
HFL-MABAC (Hesitant Fuzzy Linguistic Projection-Based MABAC with Bonferroni Mean (Sun et al. 2018)) is a ranking multi-criteria decision-making (MCDM) method introduced by Sun, R., Hu, J., Zhou, J., Chen, X. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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When to use it
HFL-MABAC ranks alternatives based on performance scores. Higher score = better rank.
Strengths & limitations
Strengths
- Follows a transparent, reproducible computational procedure that can be audited step by step.
- Handles multiple criteria of differing scales and units within a single decision matrix.
Limitations
- May exhibit rank reversal when alternatives are added to or removed from the set.
Sources
- Sun, R., Hu, J., Zhou, J., Chen, X. (2018). A Hesitant Fuzzy Linguistic Projection-Based MABAC Method for Patients' Prioritization. International Journal of Fuzzy Systems DOI: 10.1007/s40815-017-0345-7 ↗
How to cite this page
ScholarGate. (2026, June 2). Hesitant Fuzzy Linguistic Projection-Based MABAC with Bonferroni Mean (Sun et al. 2018). ScholarGate. https://scholargate.app/en/decision-making/hfl-mabac