Dynamic Pricing for Perishables

Dynamic Pricing for Perishables is the broader operations-research class of pricing problems where the value of an item declines with time and the price trajectory must adapt accordingly. The class covers fresh food (shelf-life-driven decline), fashion (season-driven decline once the collection's window closes), electronics (new-generation arrival), and hotel rooms or airline seats (perish at the arrival or departure moment). The trajectory may be monotonically decreasing (Markdown Pricing — Smith-Achabal 1998; Bitran-Mondschein 1997) when the product is stock-bound and the season closes; or up-down dynamic (Revenue Management — Talluri-van Ryzin 2004) when the capacity is fixed and the product perishes on a time-anchored event. Methodologies include deterministic and stochastic dynamic programming, multi-product MIP, and modern Bayesian learning + Thompson sampling for online repricing. The canonical reference book is Talluri and van Ryzin (2004) *The Theory and Practice of Revenue Management*; the famous fast-fashion deployment is Caro and Gallien (2012) *Operations Research*. Typical constraints include monotone-decrease (for markdown) or non-negative price (for both), maximum-discount cap (for brand image), capacity (for RM), and demand stochasticity. The class distinguishes itself from static-pricing newsvendor-type decisions where the order quantity is set once before the selling horizon and the price is held constant.