Fuzzy MARCOS — Fuzzy extension of MARCOS
FUZZY-MARCOS (Fuzzy MARCOS — Fuzzy extension of MARCOS) is a ranking multi-criteria decision-making (MCDM) method introduced by Chen, C. T. in 2000. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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When to use it
fuzzy-marcos extends MARCOS to handle Fuzzy uncertainty. All arithmetic operations (normalisation, weighting, distance computation) are performed using Triangular Fuzzy Number (TFN: l, m, u) algebra. The final scores are defuzzified via centroid (l+m+u)/3 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.
- 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
- Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems DOI: 10.1016/S0165-0114(97)00377-1 ↗
How to cite this page
ScholarGate. (2026, June 2). Fuzzy MARCOS — Fuzzy extension of MARCOS. ScholarGate. https://scholargate.app/en/decision-making/fuzzy-marcos
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