Z-Number Analytic Hierarchy Process
Z-AHP (Z-Number Analytic Hierarchy Process) is a weighting multi-criteria decision-making (MCDM) method introduced by Mahammad Nuriyev (Khazar University, Baku, Azerbaijan) in 2020. 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
Z-AHP outputs criterion importance weights (sum=1). Higher weight = more important. Pair with any alternative-ranking method (Z-TOPSIS, Z-PROMETHEE per Nuriyev's hybrid) that consumes a weight vector. For multi-level hierarchies, compute weights level-by-level and combine via Saaty's hierarchical aggregation.
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
This section is available to Pro members. Upgrade to Pro
Sources
- 1.Nuriyev, M. (2020). Z-numbers Based Hybrid MCDM Approach for Energy Resources Ranking and Selection. International Journal of Energy Economics and Policy
You have read it. What now?
Cite this page
ScholarGate. (2026, June 2). Z-AHP. ScholarGate. https://scholargate.app/decision-making/z-ahp