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Ranking
Fuzzy RAWEC - Fuzzy extension of RAWEC
Fuzzy outranking/ranking - Triangular Fuzzy Number (TFN: l, m, u)
Chen, C. T.2000doi:10.1016/S0165-0114(97)00377-1 ↗
Overview
fuzzy-rawec extends RAWEC to handle Fuzzy uncertainty. All arithmetic operations (normalisation, weighting, distance computation) are performed using Triangular Fuzzy Number (TFN: l, m, u) algebra. The final scores are defuzzified via centroid (l+m+u)/3 before ranking.
- Output
- utility, higher is better
- Data
- Fuzzy (TFN), uncertainty tuples complete
- Weights
- Needs a weight source
- Size
- 2+ alternatives, 3-10 criteria works best
- Used for
- Fuzzy (Triangular) MCDM, MAGDM under epistemic uncertainty, expert-driven evaluation with linguistic terms
Look elsewhere when
- •Crisp data sufficient - use base RAWEC directly (avoid unnecessary uncertainty layer)
- •Aggregation operator (PFWA/PFOWA/etc.) not specified - output ambiguous
Assumptions to verify
- Decision matrix entries are valid Fuzzy (Triangular) 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 TFN: l ≤ m ≤ u, all ≥ 0 before computation.
Defuzzification method affects ranking: centroid (l+m+u)/3 is the canonical choice but alternatives exist.
Works with
Commonly takes its weights from
Its derived weights can feed
How to cite
Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems. https://doi.org/10.1016/S0165-0114(97)00377-1
System ID, as it appears in reports and the API
FUZZY-RAWEC