Airline Timetable Development and Fleet Assignment Incorporating Passenger Choice

Abstract

Flight timetabling can greatly impact an airline’s operating profit, yet data-driven or model-based solutions to support it remain limited. Timetabling optimization is significantly complicated by two factors. First, it exhibits strong interdependencies with subsequent fleet assignment decisions of the airlines. Second, flights’ departure and arrival times are important determinants of passenger connection opportunities, of the attractiveness of each (nonstop or connecting) itinerary, and, in turn, of passengers’ booking decisions. Because of these complicating factors, most existing approaches rely on incremental timetabling. This paper introduces an original integrated optimization approach to comprehensive flight timetabling and fleet assignment under endogenous passenger choice. Passenger choice is captured by a discrete-choice Generalized Attraction Model. The resulting optimization model is formulated as a mixed-integer linear program. This paper also proposes an original multi-phase solution approach, which effectively combines several heuristics, to optimize the network-wide timetable of a major airline within a realistic computational budget. Using case study data from Alaska Airlines, computational results suggest that the combination of this paper’s model formulation and solution approaches can result in significant profit improvements, as compared to the most advanced incremental approaches to flight timetabling. Additional computational experiments based on several extensions also demonstrate the benefits of this modeling and computational framework to support various types of strategic airline decision-making in the context of frequency planning, revenue management, and post-merger integration.

Keywords: Airline Scheduling, Flight Timetabling, Discrete Choice, Mixed Integer Programming