qR-COPRAS — q-Rung Orthopair extension of COPRAS
QR-COPRAS (qR-COPRAS — q-Rung Orthopair extension of COPRAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Yager, R. R. 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
This section is available to Pro members. Upgrade to Pro
How it works
This section is available to Pro members. Upgrade to Pro
When to use it
QR-COPRAS Pattern B: each q-ROFN cell is reduced to a crisp score s_ij = μ^q − ν^q at F1, shifted to [0, 2] via s̃ = s + 1 (so the cost denominator in F3 stays positive), column-sum normalised, and weighted. F2 splits the weighted row into benefit (S_i^+) and cost (S_i^-) sums. F3 computes Q_i = S_i^+ + (Σ_k S_k^-)/(S_i^- · Σ_k(1/S_k^-)) — the larger Q_i, the better. F4 reports N_i = Q_i / max Q × 100% as a utility-degree summary. Ranking is descending in Q_i (equivalently, in N_i). Cost direction is handled by the Ω_c partition at F2, NOT by q-ROFN complement at F1 (the s + 1 shift assumes sc
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
This section is available to Pro members. Upgrade to Pro
Sources
- 1.Yager, R. R. (2017). Generalized orthopair fuzzy sets. IEEE Transactions on Fuzzy Systems
You have read it. What now?
Cite this page
ScholarGate. (2026, June 2). QR-COPRAS. ScholarGate. https://scholargate.app/decision-making/qr-copras