Evaluation Based on Distance from Average Solution
EDAS (Evaluation Based on Distance from Average Solution) is a ranking multi-criteria decision-making (MCDM) method introduced by Keshavarz Ghorabaee, M., Zavadskas, E. K., Olfat, L., Turskis, Z. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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When to use it
AS_i ∈ [0,1]. Higher AS means the alternative is more above the average solution (positively) and less below it (negatively). EDAS is robust when the ideal and anti-ideal cannot be identified reliably, since it uses the average as reference instead.
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.
- 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.
Sources
- 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 DOI: 10.15388/Informatica.2015.57 ↗
How to cite this page
ScholarGate. (2026, June 2). Evaluation Based on Distance from Average Solution. ScholarGate. https://scholargate.app/en/decision-making/edas
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