Smart Inventory Strategies for Handling Deteriorating Goods in Time-Critical Markets

Abstract

This study looks at the rising difficulty of inventory control for items that go bad. These items include drugs, fresh food, and tech parts that lose value over time. The main goal is to create a plan that makes order sizes better. This plan considers both physical decay and the need to meet time-based market demand. Using mathematical models, the study builds on the basic Economic Order Quantity (EOQ) method. It adds demand that changes over time and different rates of decay. The method uses math to find functions that lower costs. It also tests how well the model holds up when market conditions change. The results show that normal static inventory models greatly overestimate the best stock levels for things that spoil. This leads to higher holding costs and waste. But, the Smart Strategy presented matches purchase cycles with how fast the product breaks down. This lowers total system costs by 15-20%. The study finds that in markets where time is important, inventory control must change. Instead of just refilling stock, it needs to predict and sync with time. This work adds to the field by linking EOQ models with the real problems of fast product aging. It gives a solution that can grow for supply chain managers facing today's market changes.