Integrating Perishables' Shelf Life into Assortment Optimization

In perishable categories, assortment design entails a three-way trade-off among variety, profitability, and waste. Because products deteriorate over time, effective assortment management requires not only selecting the right product mix but also ensuring that items meet consumers' freshness expectations at the point of purchase. Although assortment optimization has been extensively studied, existing models typically ignore shelf life or treat it as a static availability constraint, overlooking its dynamic effect on demand, substitution, and the selling window. We address this gap by developing an assortment optimization framework that incorporates remaining shelf life (RSL) directly into consumer utility and captures RSL-driven substitution across products. Using transaction-level data from the non-dairy yogurt category of a major European grocery retailer, we estimate an RSL-aware multinomial logit model and evaluate alternative assortment strategies via simulation. Relative to a freshness-agnostic specification, the RSL-aware approach yields a 3.3% increase in expected profit under a profit maximization objective. Under a relative waste minimization objective, it reduces food waste by 0.7 percentage points. To ensure scalability in larger categories, we introduce two simple, objective-specific heuristics that use ranking rules to restrict the candidate assortment set. Despite their computational simplicity, these heuristics deliver assortments whose profit is, on average, within 1.42% of the exhaustiveenumeration reference profit and whose waste differs by only 0.04 percentage points. Overall, the results establish product freshness as a critical determinant of assortment performance. The framework links freshness-sensitive consumer behavior to operational decisions and provides retailers with practical guidance for improving both profitability and sustainability in perishable categories.