Revenue management has become an important tool in the airline, hotel, and rental car industries. We describe asymptotic properties of revenue management policies derived from the solution of a deterministic optimization problem. Our primary results state that, within a stochastic and dynamic framework, solutions arising out of a single well-known linear program can be used to generate allocation policies for which the normalized revenue converges in distribution to a constant upper bound on the optimal value. We also show similar asymptotic results for expected revenues. In addition, we describe counterintuitive behavior that can occur when allocations are updated during the booking process (updating allocations can lead to lower expected revenue). These results add to the understanding of allocation policies and help to make concrete the statement that simple policies from easy-to-solve formulations can be relatively effective, even when analyzed in the more realistic stochastic and dynamic framework.

We consider the simultaneous seat-inventory control of a set of parallel flights between a common origin and destination with dynamic customer choice among the flights. We formulate the problem as an extension of the classic multiperiod, single-flight “block demand” revenue management model. The resulting Markov decision process is quite complex, owing to its multidimensional state space and the fact that the airline’s inventory controls do affect the distribution of demand. Using stochastic comparisons, consumer-choice models, and inventory-pooling ideas, we derive easily computable upper and lower bounds for the value function of our model. We propose simulation-based techniques for solving the stochastic optimization problem and also describe heuristics based upon an extension of a well-known linear programming formulation. We provide numerical examples.

The spiral-down effect occurs when incorrect assumptions about customer behavior cause high-fare ticket sales, protection levels, and revenues to systematically decrease over time. If an airline decides how many seats to protect for sale at a high fare based on past high-fare sales, while neglecting to account for the fact that availability of low-fare tickets will reduce high-fare sales, then high-fare sales will decrease, resulting in lower future estimates of high-fare demand. This subsequently yields lower protection levels for high-fare tickets, greater availability of low-fare tickets, and even lower high-fare ticket sales. The pattern continues, resulting in a so-called spiral down. We develop a mathematical framework to analyze the process by which airlines forecast demand and optimize booking controls over a sequence of flights. Within the framework, we give conditions under which spiral down occurs.

Vascular permeability plays a key role in a wide array of lifethreatening and sight-threatening diseases. Vascular endothelial growth factor can increase vascular permeability. Using a model system for nonproliferative diabetic retinopathy, we found that pigment epithelium-derived factor (PEDF) effectively abated vascular endothelial growth factor-induced vascular permeability. A 44-amino acid region of PEDF was sufficient to confer the antivasopermeability activity. Additionally, we identified four amino acids (glutamate-101, isoleucine-103, leucine-112, and serine-115) critical for this activity. PEDF, or a derivative, could potentially abate or restore vision loss from diabetic macular edema. Furthermore, PEDF may represent a superior therapeutic approach to sepsis-associated hypotension, nephrotic syndrome, and other sight-threatening and life-threatening diseases resulting from excessive vascular permeability.