Hesitant Fuzzy Generalized Peer-Evaluation (strategy-blended cross-efficiency with BFM, Zhou-Chen-Xu-Meng 2018)
HFGPE (Hesitant Fuzzy Generalized Peer-Evaluation (strategy-blended cross-efficiency with BFM, 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
HFGPE generalises HFPE by allowing a continuous spectrum between benevolent (d=1) and aggressive (d=0) strategies. The strategy parameter d can be calibrated from historical outcomes via BFM, making the ranking data-adaptive. If no historical data is available, d=0.5 (neutral) is a reasonable default. A higher Ē_l(d*) means the alternative performs well under a realistic blend of perspectives.
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). HFGPE. ScholarGate. https://scholargate.app/decision-making/hfgpe