Sohail Sayed

Multi-Agent Reinforcement Learning for Dynamic Inventory Rebalancing and Last-Mile Fulfillment Under Supply Chain Disruptions

Experiments show that prediction must be coupled with autonomous optimization to deliver practical resilience, and show that the learned policy sustains service levels, shortens recovery time, and reduces total disruption cost relative to base-stock and single-agent baselines.