Optimization
In our most of our projects, optimization is the key word. For this purpose we create heuristic algorithms and mathematical solvers to test and optimize all kinds of systems. To determine the best control rules we use simulation to validate and fine-tune to get the best real-life results.
The rules are then implemented in TraverseBoard platform to be easily used in an the operations.
The power of simulation
As the requirements for some of our solvers are very detailed, the solvers are developed in such way that they can be used both in a simulation environment and in an operational scheduling system.
The combination of mathematics and heuristic rules together with an simulation environment will result in very powerful schedulers that will perform in real life with all possible uncertainties.
Coping with uncertainty
Mathematical optimization models can only cope with a fixed input. The result of an optimization can render the optimized schedule obsolete the moment in one of the variables changes, like a process taking just a bit longer.
As simulation can also cope with uncertainty, we are able to create more robust schedules that function much better in an dynamic environment.
