Automate and optimize airline fleet assignment
Every airline has a system that holds the published schedule and the fleet. Few have anything that decides, quickly and at full network size, which tail should fly each leg, in what order, and how to get it to its maintenance base on time. Let's solve that.
One solve covers every leg, every tail, and every maintenance check
Timefold solves tail assignment and rotation sequencing as one optimization problem. Fleet type, range, ETOPS, runway, and cabin rules decide which legs a tail can fly at all. Station continuity, minimum turnaround, tail availability, scheduled checks, and flight-hour and cycle allowances are hard constraints, so every rotation can actually be flown. Within those rules, the model minimizes total cost: fuel, delay, spill, crew changes, and swaps.
Where Timefold goes beyond rules-based tail planning
Four things decide whether a rotation holds up on the day. Timefold bakes them into the model.
Safety rules can't be traded for cost
A tail never sees a leg its range, ETOPS certification, or runway requirement rules out, and maintenance checks are hard constraints.
Delay risk is spread, not stacked
The model prices delay that carries down a rotation, so tight connections stay away from the legs most likely to run late or hit a curfew.
Weights are rates finance already tracks
Fuel price per kilogram, delay cost per minute, and spill cost per passenger set the trade-offs, not abstract scores.
IROPS replans change only what they must
Departed, pinned, and frozen legs keep their tail, and every swap away from the published rotation carries a cost.
Every tail decision moves fuel, utilization, and revenue
Which tail flies which leg decides fuel burn, how many block hours each aircraft earns, and how many passengers fit on board. Those effects compound across a network of hundreds of tails and thousands of legs.
Annual fuel cost savings
Typical gains from tail assignment optimization, on top of an already optimized fuel bill.
Block hours a day per aircraft
The range commonly cited as healthy utilization, which tighter feasible rotations help reach.
Tails where manual planning breaks down
A process that works for 20 tails falls apart as the fleet and network grow.
Annual savings from better spill modeling
A lot of money can be saved by tail assignment optimization.
Constraints the model expresses today
When scheduling works, everything works.
Less waste. More control. Teams that trust the plan.