Inventory management in modern retail is persistently challenged by the mismatch between supply and customer demand, a problem that leads to costly overstocks and lost sales from stockouts. This issue persists despite sophisticated forecasting tools, primarily due to the inherent uncertainty and volatility of consumer behavior. Lateral transshipment—the practice of moving inventory between locations at the same supply chain echelon—has emerged as a key strategy to enhance flexibility and mitigate these imbalances by creating a pooled inventory resource. This thesis develops and analyzes a reactive transshipment policy tailored for multi-location retail networks that manage products with short selling seasons and highly uncertain demand based on the paper “Approximate Dynamic Programming for Lateral Transshipment Problems in Multi‑Location Inventory Systems” by Joern Meissner and Olga V.