Probabilistic Linguistic extension of MULTIMOORA
PL-MULTIMOORA (Probabilistic Linguistic extension of MULTIMOORA) is a ranking multi-criteria decision-making (MCDM) method introduced by Wu, X. Liao, H. Xu, Z. S. Hafezalkotob, A. Herrera, F. 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
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.
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.
- Results depend on the chosen normalisation, weights, and parameter settings.
Common pitfalls
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Sources
- 1.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
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Cite this page
ScholarGate. (2026, June 2). PL-MULTIMOORA. ScholarGate. https://scholargate.app/decision-making/pl-multimoora