The network choice revenue management problem models customers as choosing from an offer-set, and the firm decides the best subset to offer at any given moment to maximize expected revenue. The resulting dynamic program for the firm is intractable and approximated by a deterministic linear...

The network choice revenue management problem models customers as choosing from an offerset, and the firm decides the best subset to offer at any given moment to maximize expected revenue. The resulting dynamic program for the firm is intractable and approximated by a deterministic linear...

The network choice revenue management problem models customers as choosing from an offer-set, and the firm decides the best subset to offer at any given moment to maximize expected revenue. The resulting dynamic program for the firm is intractable and approximated by a deterministic linear...

In many implemented network revenue management systems, a bid price control is being used. In this form of control, bid prices are attached to resources, and a product is offered if the revenue derived from it exceeds the sum of the bid prices of its consumed resources. This approach is...

In recent years, many traditional practitioners of revenue management such as airlines or hotels were confronted with aggressive low-cost competition. In order to stay competitive, these firms responded by reducing fare restrictions that were originally meant to fence off customer segments. In...

We present improved network revenue management methods that assume customers to choose according to the multinomial logit choice model with the specific feature that the sets of considered products of the different customer segments are allowed to overlap. This approach can be used to model...

We develop a new approximate dynamic programming approach to network revenue management models with customer choice that approximates the value function of the Markov decision process with a concave function which is separable across resource inventory levels. This approach reflects the...

We develop an approximate dynamic programming approach to network revenue management models with customer choice that approximates the value function of the Markov decision process with a non-linear function which is separable across resource inventory levels. This approximation can exhibit...

One of the latest developments in network revenue management (RM) is the incorporation of customer purchase behavior via discrete choice models. Many authors presented control policies for the booking process that are expressed in terms of which combination of products to offer at a given point...

The dynamic program for choice network RM is intractable and approximated by a deterministic linear program called the CDLP. When the segment consideration sets overlap, the CDLP is difficult to solve. A weaker formulation (SDCP+) is tractable and approximates the CDLP value very closely. We...