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Dynamic Airline Scheduling

Sabre Holdings, Southlake, Texas 76092
Operations Research Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
haijiang{at}alum.mit.edu
cbarnhar{at}mit.edu

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.

Key Words: airline scheduling; dynamics scheduling; demand stochasticity
History: Received: August 2007; revised: October 2008; accepted: January 2009.