Picture Fuzzy Dombi Aggregation Operators for MADM (Jana, Senapati, Pal & Yager 2019)
PIF-DOMBI (Picture Fuzzy Dombi Aggregation Operators for MADM (Jana, Senapati, Pal & Yager 2019)) is a aggregationoperator multi-criteria decision-making (MCDM) method introduced by Jana, C. Senapati, T. Pal, M. Yager, R. R. in 2019. 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
PIF-DOMBI applies the Jana et al. 2019 Picture Fuzzy Dombi aggregation family. Choose PFDWA (default, arithmetic, Eq.2) for compensatory aggregation or PFDWG (Eq.7) for geometric (less compensatory, low μ values penalized more). The ℜ ≥ 1 parameter controls trade-off: ℜ→1 approaches algebraic t-norm, ℜ→∞ approaches max/min. Score Ê(T)=(1+μ-ν)/2 ignores η (refusal/neutral); if η-sensitivity matters, prefer Wei 2017 PFWA or Cuong-Kreinovich score variants.
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.
Common pitfalls
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Sources
- 1.Jana, C., Senapati, T., Pal, M., Yager, R. R. (2019). Picture fuzzy Dombi aggregation operators: Application to MADM process. Applied Soft Computing
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Cite this page
ScholarGate. (2026, June 2). PIF-DOMBI. ScholarGate. https://scholargate.app/decision-making/pif-dombi