Hesitant Fuzzy Peer-Evaluation (benevolent / aggressive cross-efficiency, Zhou-Chen-Xu-Meng 2018)
HFPE (Hesitant Fuzzy Peer-Evaluation (benevolent / aggressive cross-efficiency, Zhou-Chen-Xu-Meng 2018)) is a dea multi-criteria decision-making (MCDM) method introduced by Zhou, W. Chen, J. Xu, Z. S. Meng, S. in 2018. 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
HFPE produces full discrimination where HFEA ties at m_e=1. The cross-efficiency column mean ĒL is a peer-reviewed score: a high ĒL means the alternative performs well not just under its own most favourable weights, but also under the weights preferred by its competitors. Benevolent strategy is more generous; aggressive is more discriminating. Choose based on decision context.
Strengths & limitations
- 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.
- 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.
Common pitfalls
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Sources
- 1.Zhou, W., Chen, J., Xu, Z. S., Meng, S. (2018). Hesitant fuzzy preference envelopment analysis and alternative improvement. Information Sciences
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ScholarGate. (2026, June 2). HFPE. ScholarGate. https://scholargate.app/decision-making/hfpe