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Home›Decision-making›Complex Fuzzy Z-Number Weighted Aggregated Sum Product Assessment
MCDMUtilityComplex fuzzy z number

Complex Fuzzy Z-Number Weighted Aggregated Sum Product Assessment

CFZN-WASPAS (Complex Fuzzy Z-Number Weighted Aggregated Sum Product Assessment) is a utility multi-criteria decision-making (MCDM) method introduced by Shahid, A. Ashraf, S. Chohan, M. S. in 2026. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.

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When to use it

CFZN-WASPAS ranks alternatives based on performance scores. Higher score = better rank.

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
  • Assumes full compensation — a strong score on one criterion can offset a weak score on another.

Sources

  1. Shahid, A., Ashraf, S., Chohan, M. S. (2026). Complex Fuzzy MARCOS and WASPAS Approaches with Z-Numbers for Augmented Reality Decision Making. Spectrum of Operational Research DOI: 10.31181/sor31202637 ↗

How to cite this page

ScholarGate. (2026, June 2). Complex Fuzzy Z-Number Weighted Aggregated Sum Product Assessment. ScholarGate. https://scholargate.app/en/decision-making/cfzn-waspas

Similar methods

CFZN-MARCOSZ-WASPASBF-WASPASHF-WASPASQR-WASPASFUZZY-WASPASWASPASP-WASPAS

Related reference concepts

Decision Support SystemsDecision MakingCriteria for Decision-Making under Risk and UncertaintyWeighted ScoresEvaluation CriteriaPolicy Analysis

Spotted an issue on this page? Report or suggest a fix →

ScholarGate — CFZN-WASPAS (Complex Fuzzy Z-Number Weighted Aggregated Sum Product Assessment). Retrieved 2026-07-21 from https://scholargate.app/en/decision-making/cfzn-waspas · Dataset: https://doi.org/10.5281/zenodo.20539026
Quick facts
Originator
Shahid, A. Ashraf, S. Chohan, M. S.
Subfamily
Utility
Year
2026
Type
Hybrid sum-product utility ranking via convex combination of WSM and WPM aggregations under complex fuzzy Z-number uncertainty
Value Space
Complex fuzzy z number
Uncertainty
hybrid
Compensation
full
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