Perishable inventory management under inventory level- and freshness-dependent demand and backroom effect

Abstract

Managing perishable inventory in grocery retailing is challenging due to limited shelf life and consumer expectations for freshness. We develop an optimization model to guide a retailer’s in-store replenishment process, where inventory is initially stored in a backroom before being moved to the shelf. Consumer demand is stochastic and depends on shelf-life and inventory level, and the retailer wants to maximize long-term discounted profit by determining optimal time to move inventory from the backroom to the shelf. We show that the optimal policy follows a threshold structure dependent on shelf inventory levels and product lifetimes. To simplify decision-making, we propose heuristics. Our analysis indicates that the optimal time to move products from backrooms to shelves is highly dependent on the characteristics of the products. The main driver of this decision is the shelf inventory level for products with long shelf-lives and small batches. On the other hand, for products with short shelf-lives and large batch-sizes, the main driver is the product lifetime. While mixing batches on the shelf can reduce waste under ideal backroom storage, displaying a single batch is more profitable when backroom deterioration is significant.