The techniques of revenue management have potential application in many industries – as long as customers view the resulting policies as being fair.

The two key resources in an IP Telephony network are the Internet Telephony Gateways (ITGs) and the IP network. These resources must be effectively managed to simultaneously provide good QoS to calls and maximize network resource utilization. This paper presents two main contributions. First, we design a call admission policy based on congestion sensitive pricing. As the load increases, this po...

In this paper, we develop a stochastic approximation algorithm for making pricing decisions in network revenue management problems. In the setting we consider, the probability of observing a request for an itinerary depends on the price for the itinerary. We are interested in finding a set of prices that maximize the total expected revenue. Our approach is based on visualizing the total expecte...

Revenue management has been successfully implemented in the airline industry since the deregulation in 1978. There have been very few comprehensive, rigorous studies of its practices and impact, however. In this paper we examine how revenue management practices affect airline performances such as loadfactor and revenue, and how revenue management practices are implemented in different market st...

The network revenue management (RM) problem arises in airline, hotel, media, and other industries where the sale products use multiple resources. It can be formulated as a stochastic dynamic program, but the dynamic program is computationally intractable because of an exponentially large state space, and a number of heuristics have been proposed to approximate its value function. Notable amongs...

Static game-theoretic models of bilateral bargaining assume that the seller knows his valuation for the item that is up for sale; that is, how the seller may determine this quantity is exogenous to these models. In this paper, we develop and analyze a stylized Markov decision process that endogenizes the seller’s computation of his marginal inventory valuation in an infinite horizon revenue man...

Revenue management (RM) is the art and science of predicting consumer behavior and optimizing price and product availability to maximize revenue. RM models, despite their success and popularity, still remain somewhat simplistic. The most critical flaw is that current RM models are designed under the assumption that demands are independent random variables. The models are readily extended to com...

Deterministic mathematical programming models that capture network effects play a predominant role in the theory and practice of airline revenue management. These models do not address important issues like demand uncertainty, nesting, and the dynamic nature of the booking process. Alternatively, the network problem can be broken down into leg-based problems for which there are satisfactory sol...

We develop two classes of optimization models to maximize revenue in a restaurant (while controlling average waiting time as well as perceived fairness) that may violate the first-come-first-serve (FCFS) rule. In the first class of models, we use integer programming, stochastic programming, and approximate dynamic programming methods to decide dynamically when, if at all, to seat an incoming pa...

A well-studied problem in the literature on airline revenue (or yield) management is the optimal allocation of seat inventory among fare classes given a demand distribution for each class. In the literature thus far, passenger demand is an exogenous parameter. However, the seat allocation decisions of one airline affect the passenger demands for seats on other airlines. In this paper we examine...