Brute-forcing a solution by generating parking plans and checking if they fill requirements is far too time-consuming to be feasible. Instead, we frame the problem as a linear mixed-integer optimisation problem, aiming to maximise robustness whilst adding business, legal and logistical requirements as linear constraints. This narrows the feasible region in which to find a solution. Dantzig’s Simplex algorithm is then used to find the solution, using an iterative process of elimination. For constraints for which no hard data is available, we estimate their values using a Gaussian Process prediction model.
From 3 hours to 30 seconds.
The solution was deployed in December 2018, but the results are already hugely impressive.
Comparing December 2018 with December 2017:
More robust against schedule changes
The new parking plan created by the model is optimal in the sense that the idle time between successive flights at the same stand is as long as possible. Therefore, when delays or exceptions inevitably occur, it is less likely that the delays will impact other flights. As the plan is more robust, delays do not snowball to other flights.
Using the new system, it’s now possible to instantly get a helicopter view of the entire airport. Parking spots, planes and busses are now shown on a single screen, which makes it easy to understand what is happening at the airport. And a single click creates a new plan, if problems appear on the horizon.
Operating an airport is a collective affair. As the parking plan is now easily presentable and familiar to everyone at the airport, collaboration and coordination between different parties at the airport is simplified.
Less CO2 emissions
The likelihood that a plane has to circle around Kittilä before a parking space becomes available has been reduced. As a result, tons of fuel is saved.