Microsoft Research | Joint Pricing and Inventory Management with Demand Learning @MicrosoftResearch | Uploaded December 2022 | Updated October 2024, 1 week ago.
2022 Data-driven Optimization Workshop: Joint Pricing and Inventory Management with Demand Learning

Speaker: Yuan Zhou, Tsinghua University

In the problem of joint pricing and inventory management the retailer makes simultaneously a price decision and an inventory order-up-to decision at the beginning of each review period. The demands are being modeled as either a parametric or nonparametric function depending on the prices.

In this talk, I will introduce two of my recent works advancing this problem: the first one deals with fixed ordering costs under the backlogging setting, with a parametric (generalized linear) demand model. The second one studies nonparametric demand models with censored demands and lost sales. The techniques involved include a novel UCB analysis over trajectories of (s,S,p) policies, and a noisy comparison oracle constructed for censored demand models.

This talk is based on the following two papers:
papers.ssrn.com/sol3/papers.cfm?abstract_id=3632475
papers.ssrn.com/sol3/papers.cfm?abstract_id=3750413