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.
Read the full method
Sign in with a free account to read this section.
Method map
The neighbourhood of related methods — select a node to explore.
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.
Sources
- Nuriyev, M. (2020). Z-numbers Based Hybrid MCDM Approach for Energy Resources Ranking and Selection. International Journal of Energy Economics and Policy DOI: 10.32479/ijeep.9950 ↗
How to cite this page
ScholarGate. (2026, June 2). Z-Number Analytic Hierarchy Process. ScholarGate. https://scholargate.app/en/decision-making/z-ahp
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- TOPSISDecision-making↔ compare
- Z-COPRASDecision-making↔ compare
- Z-EDASDecision-making↔ compare
- Z-MARCOSDecision-making↔ compare
- Z-PROMETHEEDecision-making↔ compare
- Z-TOPSISDecision-making↔ compare
- Z-VIKORDecision-making↔ compare
- Z-WASPASDecision-making↔ compare