MCDMDecision-makingRankingMath steps
Spherical extension of WASPAS
SF-WASPAS (Spherical extension of WASPAS) is a ranking multi-criteria decision-making (MCDM) method introduced by Boltürk & Kutlu Gündoğdu in 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
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
sf-waspas extends WASPAS 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
Strengths
- 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.
Limitations
- 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.Boltürk, E., Kutlu Gündoğdu, F. (2021). Prioritizing Manufacturing Challenges of a Contract Manufacturing Company for Personal Auto by Using Spherical WASPAS 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
You have read it. What now?
Cite this page
ScholarGate. (2026, June 2). SF-WASPAS. ScholarGate. https://scholargate.app/decision-making/sf-waspas