RESEARCH INTERESTS

INVITED TALKS

Introduction to Revenue Management, October 2009, Service Operations Management Class, Georgia Tech, Atlanta, GA

Forecasting Models in Revenue Management, April 2009, Supply Chain Modeling and Revenue Management Class, Georgia Tech, Atlanta, GA

Restaurant Revenue Management, November 2007, Informs Annual Meeting 2007, Seattle

State Dependent Pricing in Queues with Batch Arrivals, January 2006, Koc University, Istanbul, Turkey

Revenue Management for Buy-up Models via Stochastic Programming, November 2005, Informs Annual Meeting 2005, San Francisco

State Dependent Pricing in Queues with Batch Arrivals, November 2005, Informs Annual Meeting 2005, San Francisco

The Finite Decomposition Property in Multistation Fluid Network, October 2004, Informs Annual Meeting 2004, Denver

PUBLICATIONS

Abstract: Determination of the stability behavior of a queueing network is an important part of analyzing such systems. Gamarnik and Hasenbein (2005) have shown that if a fluid network has the finite decomposition property (FDP) and is not weakly stable, then any queueing network associated with the fluid network is not rate stable. In Gamarnik and Hasenbein’s paper, the FDP was demonstrated for two station queueing networks only.
In this paper, we show that the property holds for certain classes of queueing networks with any number of stations, thus allowing one to completely analyze the global stability of such queueing networks via the fluid model.

Abstract: It is well known that the network capacity control problem can be formulated as a dynamic programming model. However, this formulation is intractable in practice due to its size and complexity. As a result, various approximation methods are proposed in the literature. Decomposition and deterministic linear programming approximations are formulated and have been successfully used in practice. Lately, several stochastic programming (SP) approaches that take demand uncertainty into account have been published. This paper adds to recent research on SP methodologies by considering the customer’s buy-up behavior. We provide three new formulations based on different sets of assumptions. Then, we simulate demand arrival processes under four different simulation scenarios to compare the performance of each model with deterministic and randomized linear programming approximations.

Utku Yildirim,“Book Review – The Art of Pricing”,
Journal of Revenue & Pricing Management, Volume No. 6, Issue No. 2

Abstract: We investigate a problem of admission control and pricing in a firm which dominates the market. In the model, there is a single server with exponential service times and arrivals follow a compound Poisson process where the number of customers in a group is an arbitrary discrete random variable. Each arriving group calculates the expected return for the whole group using the waiting cost per unit time, the current queue length, the price provided by the firm and the substitute product reward. It is assumed the firm is a monopoly and price maker per se. The firm’s problem is to set state dependent prices for arriving batches. Once the prices have been set we formulate the admission control problem for the firm, which is a Markov decision process. Properties of the pricing and value functions are characterized, as are the optimal admission policies for a revenue maximizing firm and a social optimizer.