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Integrating the Analytic Hierarchy Process with Large Language Models for Transparent Multi-Criteria Decision-Making

Sep 2026 · 0 citations · 34 references
Computer Science

TL;DR

This study constructs a new annotated benchmark based on AHP and proposes the first end-to-end approach that enables LLMs to perform the complete AHP workflow, and shows that the method significantly improves alignment with expert judgments.

Abstract

LLMs are increasingly employed in a wide range of decision-making tasks. However, the opacity of their internal reasoning makes it difficult to validate or interpret their outputs, and the need for interpretability becomes especially critical in high-stakes settings. This study examines the decision-making capabilities of LLMs through the Analytic Hierarchy Process (AHP), a classical and widely used multicriteria decision-making framework. We construct a new annotated benchmark based on AHP and propose the first end-to-end approach that enables LLMs to perform the complete AHP workflow. Experiments in real-world decision problems in the legal and higher-education ranking domains show that our method significantly improves alignment with expert judgments.

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