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Ranking
qR-WPM - q-Rung Orthopair extension of WPM
q-Rung Orthopair outranking/ranking - q-Rung Orthopair Fuzzy Number (q-ROFN: μ, ν; μ^q+ν^q ≤ 1, q ≥ 1)
Yager, R. R.2017doi:10.1109/TFUZZ.2016.2604005 ↗
Overview
qr-wpm extends WPM to handle q-Rung Orthopair uncertainty. All arithmetic operations (normalisation, weighting, distance computation) are performed using q-Rung Orthopair Fuzzy Number (q-ROFN: μ, ν; μ^q+ν^q ≤ 1, q ≥ 1) algebra. The final scores are defuzzified via score function S = μ^q − ν^q before ranking.
- Output
- utility, higher is better
- Data
- Q-Rung Orthopair Fuzzy, uncertainty tuples complete
- Weights
- Needs a weight source
- Size
- 2+ alternatives, 3-10 criteria works best
- Used for
- Q-Rung Orthopair Fuzzy MCDM, MAGDM under epistemic uncertainty, expert-driven evaluation with linguistic terms
Look elsewhere when
- •Crisp data sufficient - use base WPM directly (avoid unnecessary uncertainty layer)
- •Aggregation operator (PFWA/PFOWA/etc.) not specified - output ambiguous
Assumptions to verify
- Decision matrix entries are valid q-Rung Orthopair Fuzzy numbers/tuples
- Underlying crisp method's compensation assumption holds in uncertain space
- All decision-maker(s) and experts use the same linguistic/uncertainty scale
Edge cases and pitfalls
Value-space violation: ensure all entries satisfy q-ROFN: μ^q + ν^q ≤ 1, q ≥ 1 (q=1→IFS; q=2→PFS) before computation.
Defuzzification method affects ranking: score function S = μ^q − ν^q is the canonical choice but alternatives exist.
Works with
Commonly takes its weights from
How to cite
Yager, R. R. (2017). Generalized orthopair fuzzy sets. IEEE Transactions on Fuzzy Systems. https://doi.org/10.1109/TFUZZ.2016.2604005
System ID, as it appears in reports and the API
QR-WPM