Z-Number Fuzzy Compromise Ranking from Distance to Ideal Solution
ZF-CRADIS (Z-Number Fuzzy Compromise Ranking from Distance to Ideal Solution) is a ranking multi-criteria decision-making (MCDM) method introduced by Puška, A. Božanić, D. Nedeljković, M. Janošević, M. in 2022. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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When to use it
Output is a compromise score Q_i per alternative — higher means the alternative is simultaneously closer to the ideal solution and farther from the anti-ideal. The top-ranked alternative is the best green supplier under the expert consensus. Pair this method with ZF-LMAW or any other Z-aware weighting source; the input decision matrix supports per-cell Z-number reliability. When experts are uncertain (low B-rating), the implicit √α down-scaling correctly reduces that cell's influence on the final 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.
Sources
- Puška, A., Božanić, D., Nedeljković, M., Janošević, M. (2022). Green Supplier Selection in an Uncertain Environment in Agriculture Using a Hybrid MCDM Model: Z-Numbers–Fuzzy LMAW–Fuzzy CRADIS Model. Axioms DOI: 10.3390/axioms11090427 ↗
How to cite this page
ScholarGate. (2026, June 2). Z-Number Fuzzy Compromise Ranking from Distance to Ideal Solution. ScholarGate. https://scholargate.app/en/decision-making/zf-cradis
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- CRITICDecision-making↔ compare
- ENTROPYDecision-making↔ compare
- FUZZY-AHPDecision-making↔ compare
- FUZZY-BWMDecision-making↔ compare
- MERECDecision-making↔ compare
- Z-AHPDecision-making↔ compare
- Z-BWMDecision-making↔ compare
- ZF-LMAWDecision-making↔ compare