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Ranking
PL-MULTIMOORA - Probabilistic Linguistic extension of MULTIMOORA
Probabilistic Linguistic multi-objective ranking - PLTS: {L_k|p_k} with expectation function + Borda aggregation
Wu, X., Liao, H., Xu, Z. S., Hafezalkotob, A., Herrera, F.2018doi:10.1109/TFUZZ.2018.2843330 ↗
Overview
PL-MULTIMOORA extends MULTIMOORA to PLTS context. It runs three sub-approaches (Ratio System, Reference Point, Full Multiplicative Form) all operating on PLEF-normalised PLTS values. The improved Borda rule aggregates the three sub-rankings into a final consensus ranking.
- Output
- rank, higher is better
- Data
- Probabilistic Linguistic, uncertainty tuples complete
- Weights
- Needs a weight source
- Size
- 3+ alternatives, 3-10 criteria works best
- Used for
- Probabilistic Linguistic MCDM, MAGDM under epistemic uncertainty, supplier selection, energy planning, technology evaluation
Look elsewhere when
- •Crisp data sufficient - use base MULTIMOORA directly
- •Single sub-approach preferred (use PL-TOPSIS or PL-VIKOR instead)
Assumptions to verify
- All PLTS entries satisfy Σ p_k ≤ 1
- FMF requires all PLEF(x̄_ij) > 0 - zero PLEF violates multiplicative form
- Linguistic term set S is the same across all experts/criteria
Edge cases and pitfalls
FMF requires PLEF(x̄_ij) > 0 for all entries; zero PLEF values cause division errors.
Works with
How to cite
Wu, X.; Liao, H.; Xu, Z. S.; Hafezalkotob, A.; Herrera, F. (2018). Probabilistic Linguistic MULTIMOORA: A Multicriteria Decision Making Method Based on the Probabilistic Linguistic Expectation Function and the Improved Borda Rule. IEEE Transactions on Fuzzy Systems. https://doi.org/10.1109/TFUZZ.2018.2843330
System ID, as it appears in reports and the API
PL-MULTIMOORA