We investigate dynamic policies for allocating inventory to correlated, stochastic demand for multiple classes, in a network environment so as to maximize total expected revenues. Typical applications include airline networks or sequential reservations for a hotel or ticketing service. We propose and analyse both theoretically and computationally a new algorithm, based on approximate dynamic programming, which provides structural insights into the optimal policy by using adaptive, non-additive bid-prices from a linear programming relaxation. We provide computational results that give insight into the performance of the new algorithm and the widely used bid price control, for several networks and demand scenarios. We extend the proposed algorithm to handle cancellations and no-shows by incorporating overbooking decisions in the underlying linear programming formulation. We report encouraging computational results that show that the new algorithm leads to higher revenues and more robust performance.

Dr Ioana Popescu is an Assistant Professor in Decision Sciences in INSEAD. She graduated with PhD in Operations Research and PhD in Applied Mathematics from MIT in 1999, under the research supervision of Prof Dimitris Bertsimas. Her current research interest focuses on Dynamic Pricing, Revenue Management and Applications of Dynamic Programming Method.
Ioana has received many awards in her career, including: a MIT Fellowship in Applied Mathematics (1995-1996), the Sarah Garth Fellowship for doctoral studies (1995-1997), Mathematics prize of the year, Wellesley College (1995), National Merit, University of Bucharest (top 1%, 1991-1993), Romanian Math Olympiads 1st prize (extended international Team, 1988-91) etc. She is also a finalist in the Nicholson Paper Competition organized by INFROMS (2000).