COmprehensive distance Based RAnking
COBRA (COmprehensive distance Based RAnking) is a ranking multi-criteria decision-making (MCDM) method introduced by Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P. 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
dC_i can be any real number. Lower dC means the alternative is closer to PIS and AS+, and farther from NIS and AS-. Rank 1 (best) is the alternative with the smallest dC.
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
- Krstić, M., Agnusdei, G. P., Tadić, S., Kovač, M., Miglietta, P. P. (2022). A Novel Axiomatic DEA-COBRA Framework for Evaluating the Sustainable Performance of Agri-Food Systems. Sustainability link ↗
How to cite this page
ScholarGate. (2026, June 2). COmprehensive distance Based RAnking. ScholarGate. https://scholargate.app/en/decision-making/cobra
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