Adapting to Evolving Requirements: Agentic AI for Retail Supply Chain Operations

arXiv:2609.03860 · cs.AI, math.OC · Submitted 2026-09-03 · Read on arXiv

cs.AI, math.OC

Submitted: 2026-09-03

Updated: 2026-09-03

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Bayesian Optimization — 9× in this paper · explained in 3 episodes
• Adaptation — 7× in this paper · explained in 1 episode
• Agentic AI — 5× in this paper · explained in 1 episode
• Correctness Rate — 5× in this paper
• End-to-End Success Rate — 4× in this paper
• Adam — 1× in this paper · explained in 2 episodes
• Admissibility — 1× in this paper · explained in 2 episodes
• Agentic Architecture — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Decision-Support Tool — 1× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes

Sources

• Context-Aware Synthesis of Optimization Pipelines for Warehouse Optimization
• A Real-Time Scalable Heuristic DSS Framework for Capacity-Constrained Retail Allocation under Supply Chain Uncertainty
• Structure-Informed Deep Reinforcement Learning for Inventory Management
• Rethinking Supply Chain Planning: A Generative Paradigm
• Democratizing Large-Scale Re-Optimization with LLM-Guided Model Patches

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