The Applied Optimization department conducts research into and develops mathematical methods and high-performance algorithms for the design, planning, and control of society’s most vital infrastructure. By integrating mathematical optimization, data science, and machine learning, we solve complex large-scale challenges in fields such as energy systems, public transport, rail, and aviation. Our work focuses on transforming theoretical foundations into scalable computational solutions that ensure the efficiency, sustainability, and resilience of these critical networks through rigorous mathematical modeling and high-performance computation.
We work in close cooperation with the professorship for Discrete Mathematics with a Focus on Discrete Optimization in Transportation at Freie Universität Berlin and the chair for Software and Algorithms for Discrete Optimization at TU Berlin.