In the second of a series of blogs on Tail Assignment we explore we dive deeper into this subject by taking a closer look at the cost model and constraints behind a Tail Assignment optimization.
In this series of blogs, we explore the dynamics of Tail Assignment. Our first blog “Unlocking Efficiency in Airline Scheduling with Tail Assignment Optimization” gave an introduction of what tail assignment means and how it can generate significant financial returns for airlines. We also explained that in order to execute this optimization effectively, airlines must take into account a wide range of factors, including costs, constraints, and more. In this blog post, we dive deeper into this subject by taking a closer look at the cost model and constraints behind a Tail Assignment optimization.
Tail Assignment is all about assigning the optimal aircraft (tail number) to each flight, in such a way that the costs are minimized, but also that all planned flights can effectively be flown while complying with all constraints.
We try to model the optimization problem as close as possible to the real-world with following components:
In order to optimize tail assignments effectively, the best way is to incorporate all the applicable costs and constraints to model the real-world as closely as possible. Airlines can then consider tweaking the weights of these costs to put more emphasis on what they want to see as an ideal result. E.g. if NOx emissions are more important than some hard cash costs, one can tweak the weight of this component in the cost function to steer the optimizer towards a further NOx emission reduction.
The resource availability and flight plan are easy to model, as those are very tangible and the constraints are a set of rules, which are defined by the airline, by the departure or arrival airport, by aircraft manufacturers and by regulators. As such these rules need to be respected and are typically modelled as autonomous, independent conditional checks.
The cost model is therefore the most complex part of the input model (when excluding the actual optimization, which will be the subject of the next blog post). Let us have a deeper look at each individual cost element:
Obviously modelling all the costs in a perfect way is impossible. As a result, every Tail Optimization will work with simplifications, by excluding certain less relevant costs and/or by calculating a specific cost element based on less variables (often derived from historical data).
It becomes quickly clear that the interactions of all these different costs on the total cost of the flight plan is untraceable for the human mind, let alone one would be able to take into account all the required constraints. The expertise of companies specialized in airline optimizations can help in setting up a model, which closely models the real-world. A powerful computer will then grind through all the possibilities, minimizing the total costs of the model, while complying to the constraints laid out in the model. This allows for quick iterations and emphasis on key topics, while making sure the airline is always operating on its best.
In the next blog post in this series, we will take a closer look at how the optimization (calculation) actually works and the sophisticated algorithms behind that.
Photo by Josh Appel on Unsplash