We consider a price-based network revenue management problem where a retailer aims to maximize revenue from multiple products with limited inventory over a finite selling season. As common in practice, we assume the demand function contains unknown parameters, which must be learned from sales...

We study a multi-period dynamic pricing problem with contextual information where the seller uses a misspecified demand model. The seller sequentially observes past demand, updates model parameters, and then chooses the price for the next period based on time-varying features. We show that model...

We study an inventory allocation problem in a two-echelon (single-warehouse multiple-retailer) setting with lost sales. At the start of a finite selling season, a fixed amount of inventory is available at the warehouse, and can be allocated to the retailers over the course of the selling horizon...