Network Revenue Management in the Presence of Demand Uncertainty

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Consider a network with fixed capacity. The owner of the network serves a heterogeneous customer population and wants to maximize the total revenue.
Customers are divided into distinct groups, each group is associated with the same unit revenue of service, resources usage, and demand uncertainty.
The network is modeled as a reservation system (i.e., unlike a queueing system, resources are not reusable in our case). The tradeoff is between the need to reserve more capacity for high-paying customers for revenue maximization and the need to contain revenue risk caused by demand uncertainty.

In this talk, I will present optimization models for this type of problems. I will discuss formulating a proper objective function and problem structure that facilitates the search for the optimal solution. I will also discuss the use of optimization models to construct customer admission policies.

Speaker Bio:

Qiong Wang has a Ph.D in Engineering and Public Policy, a master degree in Electrical and Computer Engineering, both from Carnegie-Mellon University.
He is currently a Member of Technical Staff with Industrial Mathematical and Business Analysis Group in Bell Labs' Mathematical Science Center. He research area is pricing, capacity planning, and revenue management with application to communication networks. His modeling work includes multi-stage network optimization, bandwidth provisioning in the presence of demand uncertainty, joint planning of pricing, capacity deployment, and network engineering, as well as asymptotical analysis of revenue management policy. Recently he has been working on coordination mechanisms for managing technology innovation.


  • Workflow Status: Published
  • Created By: Barbara Christopher
  • Created: 10/08/2010
  • Modified By: Fletcher Moore
  • Modified: 10/07/2016


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