MCDMDecision-makingRankingMath steps
Hesitant Fuzzy Multi-Objective Optimization by Ratio Analysis
HF-MOORA (Hesitant Fuzzy Multi-Objective Optimization by Ratio Analysis) is a ranking multi-criteria decision-making (MCDM) method introduced by Li, Z.-H. in 2014. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
Key highlights
- 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.
Intuition
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How it works
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When to use it
HF-MOORA 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.
- Assumes full compensation — a strong score on one criterion can offset a weak score on another.
Sources
- 1.Li, Z.-H. (2014). An Extension of the MULTIMOORA Method for Multiple Criteria Group Decision Making Based upon Hesitant Fuzzy Sets. Journal of Applied Mathematics
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Cite this page
ScholarGate. (2026, June 2). HF-MOORA. ScholarGate. https://scholargate.app/decision-making/hf-moora