Passenger-Centric Integrated Airline Schedule and Aircraft Recovery

Airlines are known to compete for passengers, and airline profitability heavily depends on the ability to estimate passenger demand, which in turn depends on flight schedules, fares, and the number of seats available at each fare, across all airlines. Interestingly, such competitive interactions and passenger substitution effects may not be limited to the planning stages. Existing regulations in some countries and regions impose monetary compensations to passengers in case of disruptions, altering the way they perceive the utility of other travel alternatives after the disruption starts. These passenger rights regulations may act as catalysts of passengers' response to recovered schedules. Ignoring such passenger response behavior under operational disruptions may lead airlines to develop subpar recovery schedules. We develop a passenger response model and embed it into a novel integrated optimization approach that recovers airline schedules, aircraft, and passenger itineraries while endogenizing the impacts of airlines' decisions on passenger compensation and passenger response. We also develop an original solution approach, involving exact linearization of the nonlinear passenger cost terms, combined with delayed constraint generation for ensuring aircraft maintenance feasibility and an acceleration technique that penalizes deviations from planned schedules. Computational results on real-world problem instances from two major European airlines are reported, for scenarios involving disruptions, such as delayed flights, airport closures, and unexpected grounding of aircraft. Our approach is found to be tractable and scalable, producing solutions that are superior to airline's actual decisions and highly robust in the face of passenger response uncertainty. Of particular relevance to the practitioners, our simulation results highlight that accounting for passengers' disruption response behaviors, even in a highly approximate manner, yields significant benefits to the airline compared with not accounting for them at all, which is the current state-of-the-art.

Automated summary

Airlines' profitability relies on accurately estimating passenger demand, while passenger responses to flight schedules, fares, and available seats also impact competition. Existing passenger rights regulations can affect airlines' decisions and ignoring passenger response behavior under disruptions may lead to suboptimal recovery schedules. This study develops a passenger response model and an integrated optimization approach to recover airline schedules, and demonstrates the importance of considering passenger responses for airline decision-making.