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Demand stochasticity is a major challenge for the airlines in their quest to produce profit maximizing schedules. Even with an optimized schedule, many flights on departure have empty seats while others suffer a lack of seats to accommodate passengers who desire to travel. We approach this challenge, recognizing that demand forecast quality for a particular departure date improves as it approaches, by developing a dynamic scheduling approach that reoptimizes elements of the flight schedule during the passenger booking process. The goal is to match capacity to demand given the many operational constraints that restrict possible assignments. We leverage flight retiming as a new dynamic scheduling mechanism and develop a reoptimization model that integrates both flight retiming and refleeting. Our reoptimization approach, redesigning the flight schedule at regular intervals, uses information from both revealed booking data and improved forecasts available at later reoptimizations. We conduct experiments using data from a major U.S. airline and demonstrate that significant potential profitability improvements are achieved. [ABSTRACT FROM AUTHOR]

We consider the airline fleet assignment problem involving the profit maximizing assignment of aircraft types to flight legs. Although several basic formulations have been proposed, important network considerations are insufficiently treated in these formulations and the resulting solutions are often suboptimal. We propose a new formulation and solution approach that captures network effects and generates superior solutions. We quantify the benefits of our proposed approach in a case study using data from a major United States airline. [ABSTRACT FROM AUTHOR]

This article reports that through a joint research and development effort, the United Parcel Service (UPS) and the Massachusetts Institute of Technology have produced a new optimization-based planning system for designing the UPS aircraft network. The system enables UPS planners to rapidly determine aircraft routes, fleet assignments, and package flows for its time-critical overnight delivery network. The system has yielded significant cost savings. UPS is the world's largest package delivery company, serving over 200 countries and territories, including every address in the United States. Nearly 100 additional airports serve as originating and terminating locations for packages, and more than 160 jet aircraft move nearly one million packages each night. The primary planning objective of the joint effort was to design the next-day air network at minimum cost. A number of groups at UPS face this and similar planning problems. The long range planning group develops network plans for two to 20 years in the future.