On the possibilities and limitations of LLM-based multi-agent systems for multi-criteria decision-making in healthcare operations management
Multi-criteria models for healthcare operations need weights that express how stakeholders trade off patient waiting time, provider workload, and operating cost, but these weights are difficult to quantify. Teams of large language model (LLM) agents, each prompted to represent a stakeholder, have been used to supply them. We propose a framework for assessing the reliability of LLM-generated preferences as inputs to multi-objective optimization and quantifying how their uncertainty affects decisions. We study explicit preferences by asking agents to rate the importance of the criteria in an outpatient appointment scheduling problem, and implicit preferences by inferring trade-offs from the...
| Authors | Marco Boresta, Tommaso Giovannelli, Sepehr Namirad et al. |
|---|---|
| Primary category | math.OC |
| Published | 16 October 2026 |
| Last updated at source | 16 October 2026 |
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