# Inventory

Thursday, October 4, 2018 - 4:00pm - 4:45pm

Cong Shi (University of Michigan)

We consider a periodic-review single-product inventory system with lost-sales and positive lead times under censored demand. In contrast to the classical inventory literature, we assume the firm does not know the demand distribution a priori, and makes adaptive inventory ordering decision in each period based only on the past sales (censored demand) data. The standard performance measure is regret, which is the cost difference between a feasible learning algorithm and the clairvoyant (full-information) benchmark.

Thursday, October 4, 2018 - 2:00pm - 2:45pm

Xin Chen (University of Illinois at Urbana-Champaign)

We consider a joint pricing and inventory control problem with positive replenishment lead times. Although this fundamental problem has been extensively studied in the literature, the structure of the optimal policy remains poorly understood. In this work, we propose a class of so-called constant-order contingent pricing policies with provable performance. Under such a policy, a constant-order amount of new inventory is ordered every period and a pricing decision is made based on the on-hand inventory.

Monday, May 7, 2018 - 3:00pm - 3:30pm

Chao Zhu (University of Wisconsin, Milwaukee)

This work considers an optimal inventory control problem using a long-term average criterion. In absence of ordering, the inventory process is modeled by a one-dimensional diffusion on some interval of $(-\infty, \infty)$ with general drift and diffusion coefficients and boundary points that are consistent with the notion that demands tend to reduce the inventory level. Orders instantaneously increase the inventory level and incur both positive fixed and level dependent costs. In addition, state-dependent holding/backorder costs are incurred continuously.

Friday, December 10, 2010 - 1:25pm - 2:25pm

A widely used model in online advertising industry is the one in which advertisers pre-purchase a reservation package of online inventory on content sites owned by the publishers (e.g., CNN, amazon, etc.). This package consists of specified inventory bundles of various types that are priced differently and differ in various properties including their expected effectiveness (e.g., Click Through Rate).