Rough-SAW — Rough extension of SAW
ROUGH-SAW (Rough-SAW — Rough extension of SAW) is a ranking multi-criteria decision-making (MCDM) method introduced by Stević, Ž. Pamučar, D. Zavadskas, E.K. Ćirović, G. Prentkovskis, O. in 2017. 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-saw extends SAW to handle Rough uncertainty. All arithmetic operations (normalisation, weighting, distance computation) are performed using Rough number (lower approximation L, upper approximation U) algebra. The final scores are defuzzified via midpoint (L+U)/2 before 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.
- Assumes full compensation — a strong score on one criterion can offset a weak score on another.
Common pitfalls
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Sources
- 1.Stević, Ž., Pamučar, D., Zavadskas, E.K., Ćirović, G., Prentkovskis, O. (2017). The Selection of Wagons for the Internal Transport of a Logistics Company: A Novel Approach Based on Rough BWM and Rough SAW Methods. Symmetry
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Cite this page
ScholarGate. (2026, June 2). ROUGH-SAW. ScholarGate. https://scholargate.app/decision-making/rough-saw