We consider a periodic-review inventory control problem for the Multi-Warehouse Multi-Store system with lost sales. We focus on a time horizon during which the system receives no external replenishment. Specifically, each warehouse has a finite initial inventory at the beginning of the horizon,...

We consider the setting of a firm operating multiple warehouses and multiple stores where each warehouse is endowed with an initial non-replenishable inventory. There is a finite selling horizon and, at the beginning of each period, the firm needs to decide for each store how many units of...

We propose an asymptotically optimal heuristic, which we termed the Randomized Assignment Control (RAC) for restless multi-armed bandit problems with discrete-time and fi nite states. It is based on a linear programming relaxation to the original stochastic control formulation. In contrast to...

We consider a multi-period planning problem faced by a firm that must coordinate the production and allocations of batches to end products for multiple markets. Motivated by a problem faced by a biopharmaceutical firm, we model this as a discrete-time inventory planning problem where in each...

We consider a pricing problem for a set of products displayed on a list. We assume a general cascade click model, in which customers examine the products in a decreasing order of display, from the top to (potentially) the bottom of the list. At each step, customers can decide to either purchase...

Service level constraint is often used as a metric to directly control the quality of service (e.g., managing the probability of stock-out) in practice. Many inventory problems with service level constraints are often difficult to solve and are typically approximated by deterministic...

Assortment selection is one of the most important decisions faced by retailers. Most existing papers in the literature assume that customers select at most one item out of the offered assortment. While this is valid in some cases, it contradicts practical observations in many shopping...