Cost-Optimal Foundation Model Deployment Portfolio for Transportation Management
Foundation models, including large language models (LLMs) and vision-language models (VLMs), are increasingly used for transportation management center (TMC) tasks such as anomaly detection, incident reporting, and traveler information. Deploying multiple such models across TMC functions raises a portfolio question: which model should serve each function, in which deployment mode, and under what shared hardware budget? We formulate this as the Foundation Model Deployment Portfolio (FMDP) problem, a mixed-integer program minimizing total cost of ownership (TCO) subject to per-function quality, latency, and safety constraints over shared GPU capacity. We prove the problem NP-hard by reducti...
| Authors | Xi Cheng, Ke Liu, Siyuan Feng et al. |
|---|---|
| Primary category | cs.AI |
| Published | 14 July 2026 |
| Last updated at source | 14 July 2026 |
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