MCDMDecision-makingRankingMath steps
2-Tuple Linguistic Neutrosophic EDAS
L2T-EDAS (2-Tuple Linguistic Neutrosophic EDAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Wang, P., Wang, J., Wei, G. in 2019. 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
l2t-edas extends L2T-EDAS to handle Linguistic uncertainty. All arithmetic operations (normalisation, weighting, distance computation) are performed using 2-Tuple Linguistic Variable (2TL: (s_i, α)) algebra. The final scores are defuzzified via Δ^{-1}(s_i, α) = i + α before ranking.
Strengths & limitations
Strengths
- 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.
Limitations
- 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.Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3), 435-451. [Canonical EDAS source; cited in place of the retracted Wang et al. (2019) 2-tuple linguistic neutrosophic EDAS paper, doi:10.3233/JIFS-179223.]
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Cite this page
ScholarGate. (2026, June 2). L2T-EDAS. ScholarGate. https://scholargate.app/decision-making/l2t-edas