Probabilistic Hesitant extension of VIKOR
PHF-VIKOR (Probabilistic Hesitant extension of VIKOR) is a ranking multi-criteria decision-making (MCDM) method introduced by Zhang, S. Xu, Z. S. He, Y. in 2017. 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
phf-vikor extends VIKOR to handle Probabilistic Hesitant uncertainty. All arithmetic operations (normalisation, weighting, distance computation) are performed using Probabilistic Hesitant Fuzzy Element (PHFE: {γ|p} pairs) algebra. The final scores are defuzzified via E[PHFE] = Σ γ_k p_k before ranking.
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.Zhang, S., Xu, Z. S., He, Y. (2017). Operations and integrations of probabilistic hesitant fuzzy information in decision making. Information Fusion
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Cite this page
ScholarGate. (2026, June 2). PHF-VIKOR. ScholarGate. https://scholargate.app/decision-making/phf-vikor