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Airline scheduling is a complex process requiring countless variables (flight routes, crew, aircraft and airport restrictions, aircraft maintenance requirements…​) to be defined and optimized in order to create the best possible schedule.

One critical component of airline scheduling is tail assignment optimization, which can help airlines unlock significant efficiency gains and cost reductions.

Tail Assignment is the problem of assigning each individual aircraft (identified by its tail number) to each flight in an optimal way. By optimizing tail assignments, airlines can fly their existing fleet in the most efficient way, by reducing fuel consumption (thus also lowering carbon emissions), improving aircraft utilization (fly more with the same number of aircrafts), and reducing navigation fees, landing fees, maintenance costs and more…​ Additionally, optimized tail assignments can help airlines, by creating a more robust schedule, to reduce (or even avoid) costly delays and cancellations.

The term “Tail Assignment” is used in two contexts:

• On the one hand we have the “Planning Tail Assignment” (or also called “Aircraft routing”, “Aircraft Assignment” or “Aircraft Scheduling”), which is done several weeks or even months upfront. Since at this moment, we do not know the future operational condition of each airplane yet, only the planned (recurring) maintenance constraints are considered.
• On the other hand we have the “Operational Tail Assignment“, which is done in the days leading to the day of operation and takes into account the real availability (operational condition) of the fleet, last-minute changes to the schedule, actual bookings and many more…​

Both contexts require similar optimizations, except that in the operational tail assignment there is more and better information available and the crew scheduling has already been executed, so much more info can (and should) be taken into account. This in contrast to “Planning Tail Assignment”, which is usually done before the crew scheduling.

Just like other types of scheduling, tail assignment is an optimization problem, which due to the high amount of degrees of freedom (factors or variables), results in an almost infinite number of possible suitable outcomes. Sophisticated mathematical models allow to efficiently converge towards an optimal solution.

The factors to be considered include aircraft availability, crew availability, airport restrictions, work regime constraints, operational costs, maintenance needs, fuel consumption, and more. By considering all of these factors and weighing them against each other, tail assignment optimization software can generate an optimized schedule that minimizes costs and maximizes efficiency.

To understand more clearly which gains tail assignment can bring, we should consider the typical cost structure (obviously this will vary a lot) of a sample airline:

• About 65% of the operating costs are flight operating costs, i.e. costs related to aircraft flying operations. This includes crew, fuel, maintenance and aircraft ownership. This 65% can roughly be split in about 40-45% labor, 35% fuel, 15-20% aircraft ownership and 5% maintenance.
• About 20% of the operating costs are ground operating costs, i.e. costs for servicing passengers and the aircraft in the airports. This includes aircraft landing fees and reservations/sales charges.
• About 15% of the operating costs are system operating costs, i.e. marketing, administrative and general overhead items.

This split-up shows that reducing fuel consumption, pilot or cabin crew labor costs or aircraft maintenance costs even by a few percentage can generate enormous cost savings and this is exactly what good tail assignment optimization software can deliver.

In our next blog we will dive into the cost model and constraints behind the tail assignment optimization.

Photo by Anna Gru on Unsplash