The planning of the route network of an airline is critical for success. It represents the core of the airline and is its most cricital success factor. Network planning requires the combination of airline experience and industry data with models for costs, yields, statistical data and more.
An optimal network will maximize yields and, simultaneously, minimize costs, while safeguarding its robustness. It is a critical task because of the impact on the bottom line and should not be left to hands-on experience alone.
The model can be formulated as a mathematical optimization problem. The motion of the crew and aircraft can be described by binary variables on a time-space graph representation. The yields and costs can be described in detail. Aircraft and passenger flows, slot restrictions, maintenance requirements and many other aspects of realistic operations can be expressed. This results in a large-scale optimization challenge that is solved by advanced graph algorithms which run on our high-performance computing infrastructure.
Motulus.aero has developed proprietary algorithms that can solve these planning problems to the fine-grained details. The rapid throughput makes it possible to easily explore alternative scenarios and predict the yields and corresponding costs, while unlocking hidden synergies.
Create a yield model that, for example, maximizes connections at the hub, generates holiday patterns or adds passenger demand to the equation.
Insert costs related to aircraft, crew, ground handling or any other network related costs.
Add statistical data on departure and arrival delays, flight and taxi times, turnaround times or any other network related data.
Apply slot, demand, maintenance or any other constraints which ensure that the optimized network can be flown in real life.
Crew motion is added to the equation in order to anticipate crew related costs further downstream the planning chain.
No need for on-site server infrastructure, thereby reducing IT-related costs to a minimum. Benefit from the computing power of the cloud, giving unlimited flexibility and scalability.
Solve what others struggle with. Quadratic synergies are the most difficult to model in network analysis. Our solver has proven it can.
You’re not on your own. Our optimization experts will help you create, finetune and solve your model.