Revenue management (RM) problems with full probabilistic information are well studied. However, as RM practice spreads to new businesses and industries, there are more and more applications where no or only limited information is available. In that respect, it is highly desirable to develop...

To maintain a competitive edge, companies today must be able to efficiently allocate resources to optimally commit and fulfill requested orders. As such, order processing and resource allocation models have become increasingly sophisticated to handle the complexity of these decisions. In our...

While airport congestion has long been viewed as a major air traffic management problem in the United States, congestion in the en route airspace is drawing an increasing amount of attention. Sources of en route congestion, such as severe weather, often cause the Federal Aviation Administration...

In the paper, we summarize the results of a project that was motivated by the expiration of the “High Density Rule,” which defined the slot controls employed at New York’s LaGuardia Airport for more than 30 years. The scope of the project included the analysis of several administrative...

Revenue management (RM) is one area of research and practice that has gained significant attention in the past decade. The practice originated in the airline industry, where the idea was to maximize revenues obtained from a fixed amount of resources through differentiation/segmentation and...

The U.S. National Airspace System (NAS) is inherently highly stochastic. Yet,many existing decision support tools for air traffic flow management take a deterministic approach to problem solving. In this study, we focus on the flight departure delays because such delays serve as inputs to many...