The fleet assignment problem: solving a large-scale integer program
Mathematical Programming: Series A and B
Daily aircraft routing and scheduling
Management Science
Airline Fleet Assignment with Time Windows
Transportation Science
A Stochastic Model of Airline Operations
Transportation Science
Itinerary-Based Airline Fleet Assignment
Transportation Science
Airline Crew Scheduling with Time Windows and Plane-Count Constraints
Transportation Science
Revenue Management of Flexible Products
Manufacturing & Service Operations Management
Passenger Flow Model for Airline Networks
Transportation Science
Robust airline schedule design in a dynamic scheduling environment
Computers and Operations Research
Reallocation problems in scheduling
Proceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures
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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.