Rough-EDAS — Rough extension of EDAS
ROUGH-EDAS (Rough-EDAS — Rough extension of EDAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Paul, V.K. Chakraborty, S. Chakraborty, S. in 2022. 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
rough-edas (IRN-EDAS) extends EDAS to handle two-interval rough numbers [[lL,lU],[uL,uU]]. ALL intermediate quantities — AV, PDA, NDA, VP, VN, SP, SN, NSP, NSN, AS — are maintained as full IRN throughout. Two distinct subtraction rules apply: cross-paired for (x−av) and same-level for (av−x). Division: [[a,b],[c,d]]/[[e,f],[g,h]]=[[a/h,b/g],[c/f,d/e]]. Final ranking converts IRN(AS_i) to crisp via boundary intersection points (Eq.39-46), not midpoint.
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.
Common pitfalls
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Sources
- 1.Paul, V.K., Chakraborty, S., Chakraborty, S. (2022). An Integrated IRN-BWM-EDAS Method for Supplier Selection in a Textile Industry. Decision Making: Applications in Management and Engineering
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Cite this page
ScholarGate. (2026, June 2). ROUGH-EDAS. ScholarGate. https://scholargate.app/decision-making/rough-edas