ahp-method

What problem does it solve?

The Analytic Hierarchy Process (AHP) provides a principled way to derive weights from subjective judgments by constructing a pairwise comparison matrix and extracting weights via the eigenvector method, enabling consistent decision making.

Core Features & Use Cases

• Pairwise weight extraction: Build and analyze a pairwise comparison matrix to produce a weight vector that sums to 1.
• Consistency check: Compute the Consistency Index and Consistency Ratio to assess judgment reliability and identify inconsistencies.
• Integration potential: Combine with objective weighting methods (e.g., entropy) or downstream scoring workflows (e.g., TOPIS) for blended analysis.
• Use Case: Prioritize design criteria or vendor selections where stakeholder judgments drive importance rankings.

Quick Start

To begin, prepare a small pairwise comparison matrix and run the ahp_method to obtain weights and the CR. The function returns a weights vector, the computed CR, and a flag indicating whether the judgments are consistent.