An efficient airline re-fleeting model for the incremental modification of planned fleet assignments

Airlines typically manage their annual business cycle by subdividing the year into a sequence of scheduling periods that span about a month each. Fleet assignment represents an important step in the planning process for each new scheduling period and is usually undertaken using computer-based optimization models. Once an initial fleet assignment solution is achieved and before ‘freezing’ the assignments, planners spend significant effort in analyzing, modifying, and committing the individual components of the solution throughout the flight network. This manual step results in local modifications to the initial solution, and is necessary to reflect business judgement calls that cannot be captured by the optimization model. In addition, planners find it imperative to modify the initial fleet assignment solution to react to inevitable changes to the planning environment related to the planned schedule, demand forecast, number of available aircraft, crew staffing levels, and a host of other scheduling constraints. The above-described process of incrementally fine-tuning and modifying the initial fleet assignment solution is referred to as re-fleeting. It is characterized by (1) the requirement of quick solution time to allow frequent re-fleeting exercises, (2) the need for multiple alternative high-quality solutions to choose from, and (3) the constraint that the new solution differs from the prior one in a controlled and limited fashion. We demonstrate in this paper that global fleet assignment model formulations can be used to address the re-fleeting problem in an effective fashion.