Rough-WASPAS — Rough extension of WASPAS
ROUGH-WASPAS (Rough-WASPAS — Rough extension of WASPAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Stojić, G. Stević, Ž. Antuchevičienė, J. Pamučar, D. Vasiljević, M. in 2018. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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When to use it
ROUGH-WASPAS (Stojić et al. 2018) extends WASPAS to rough number intervals [L,U]. Normalization uses rough interval divisor [max_L, max_U] (not scalar max). WSM and WPM operate entirely in rough interval arithmetic with rough interval weights [w^L_j, w^U_j]. The combined score A_i is kept as a rough interval via data-driven λ (itself a rough interval computed from Eq.17); defuzzification to crisp midpoint (A^L+A^U)/2 occurs only at the final ranking step. Weights must be rough AHP intervals (or equivalent rough weight source). Sensitivity on λ: setting λ=[0.5, 0.5] gives slightly lower scores
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
- Stojić, G., Stević, Ž., Antuchevičienė, J., Pamučar, D., Vasiljević, M. (2018). A Novel Rough WASPAS Approach for Supplier Selection in a Company Manufacturing PVC Carpentry Products. Information DOI: 10.3390/info9050121 ↗
How to cite this page
ScholarGate. (2026, June 2). Rough-WASPAS — Rough extension of WASPAS. ScholarGate. https://scholargate.app/en/decision-making/rough-waspas
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