Fall 2010 Seminar Series

DATE:October 14th
LOCATION: E62-550
TIME: 4:15pm
Reception immediately following in same room

SPEAKER:
Andrew Lim

TITLE
Decentralized Control of Stochastic Dynamic Resource Allocation Problems

ABSTRACT
Consider a stochastic service system consisting of multiple pricing agents and a service agent where pricing agents dynamically control the customer arrival rate and the service agent controls the rate at which customers are processed. With the aid of transfer/revenue sharing contracts, we show that this integrated problem can be decoupled into a dynamic pricing problem for each of the pricing agents and a service rate control problem for the service agent, and that contracts can be specified such that decentralized agent level optimization delivers centrally optimal policies. This property is shown to be robust to mis-specification by each of the agents of the impact of other agents on the system and does not require any of the agents to reveal private information (demand models, etc). An iterative algorithm for computing centralized contracts will also be presented and shown to converge to centralized optimality. A key feature of this algorithm is that its implementation does not require agents to reveal private information. Time permitting, extensions to other stochastic dynamic resource allocation problems, such as dynamic optimal portfolio selection with heterogeneous decentralized agents and coordination of airline alliances, will also be discussed.