Spherical extension of CODAS
SF-CODAS (Spherical extension of CODAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Karaşan, Boltürk & Kutlu Gündoğdu (book chapter); earlier Kutlu Gündoğdu-Kahraman 2019c JMVLSC in 2019 / 2021. 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
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How it works
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When to use it
sf-codas extends CODAS to handle Spherical uncertainty. All arithmetic operations (normalisation, weighting, distance computation) are performed using Spherical Fuzzy Set (SFS: μ, ν, π; μ²+ν²+π² ≤ 1) algebra. The final scores are defuzzified via score function S = μ² − ν² 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.
- Assumes full compensation — a strong score on one criterion can offset a weak score on another.
Common pitfalls
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Sources
- 1.Karaşan, A., Boltürk, E., Kutlu Gündoğdu, F. (2021). Assessment of Livability Indices of Suburban Places of Istanbul by Using Spherical Fuzzy CODAS Method. In: Kahraman C., Kutlu Gündoğdu F. (eds.) Decision Making with Spherical Fuzzy Sets — Theory and Applications. Studies in Fuzziness and Soft Computing vol. 392. Springer
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Cite this page
ScholarGate. (2026, June 2). SF-CODAS. ScholarGate. https://scholargate.app/decision-making/sf-codas