Offline Dynamic Inventory and Pricing Strategy: Addressing Censored and Dependent Demand

ArXi:2504.09831v2 Announce Type: replace-cross In this paper, we study the offline sequential feature-based pricing and inventory control problem where the current demand depends on the past demand levels and any demand exceeding the available inventory is lost. Our goal is to leverage the offline dataset, consisting of past prices, ordering quantities, inventory levels, covariates, and censored sales levels, to estimate the optimal pricing and inventory control policy that maximizes long-term profit.