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1191. Simple Policies for Joint Pricing and Inventory Management
Invited abstract in session TC-59: Pricing Strategies, stream Pricing and Revenue Management.
Tuesday, 12:30-14:00Room: S08 (building: 101)
Authors (first author is the speaker)
| 1. | Yeqing Zhou
|
| OPAC, Eindhoven University of Technology | |
| 2. | Adam Elmachtoub
|
| Industrial Engineering and Operations Research, Columbia University | |
| 3. | Harsh Sheth
|
| Columbia University |
Abstract
We study the fundamental joint pricing and inventory control problem, where the customers are price sensitive. In the continuous review infinite horizon setting, the optimal policy is known to be an (s, S, p) policy, and the optimal price changes for every inventory state. We consider policies with only a small number of prices offered and compare these policies to the optimal policy. When customer valuations follow an MHR distribution, we provide policies with theoretical guarantees for revenue and costs. In the lost sales case, we show that there exists a single price policy that achieves at least as much revenue as the optimal dynamic policy while incurring costs at most sqrt(1+lnS) times more. The cost ratio is improved to 1.225 when the valuation distribution is uniform. When backlogging is allowed, we show that a three-price policy can achieve similar guarantees.
Keywords
- Revenue Management and Pricing
- Inventory
- Stochastic Models
Status: accepted
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