AlphaInventory: Evolving White-Box Inventory Policies via Large Language Models with Deployment Guarantees

ArXi:2605.00369v1 Announce Type: cross We study how large language models can be used to evolve inventory policies in online, non-stationary environments. Our work is motivated by recent advances in LLM-based evolutionary search, such as AlphaEvolve, which nstrates strong performance for static and highly structured problems such as mathematical discovery, but is not directly suited to online dynamic inventory settings. To this end, we propose AlphaInventory, an end-to-end inventory-policy evolution and inference framework grounded in confidence-interval-based certification.