Our effective methodology includes statistical techniques, stochastic and machine-based optimisation (e.g. evolutionary multi-objective optimisation), macro- and microeconomic analyses as well as modelling and simulation of aviation processes in the air and on the ground. Approaches from the area of artificial intelligence and machine learning are also applied to complex processes surrounding aviation operations (GANNs, Reinforcement -NN), as we develop computer supported simulation models and research new methods within the field.

The dynamics of passenger flows, capacity management and analysis, delay propagation, revenue management, hub-and-spoke load balancing, network analyses and simulation of baggage processes are among the many processes analysed within our projects.

• Airport Capacity Modelling and Security Indicators
  The infrastructure and operative planning of airports must be able to accommodate passenger demand to avoid losses in punctuality, safety, security and general quality of service
• Profit Cycles in the Airline Industry Prediction with Convolutional Networks
  Modern statistical and algorithmic methodology allow the detection, analysis and optimisation of micro- and macroeconomic operational dependencies.