The core competence of the Optimization division is the individual solution of planning and decision problems in logistics, engineering and life sciences, coordinated with customers. Methodically, the solution approaches are based on a close interlocking of:
By this we understand the model- or data-based virtual structure generation under consideration of restrictions and free design parameters as well as the identification of quality and cost measures for the evaluation of the structures to be optimized.
The core competence of our department is the development and implementation of customized optimization methods for the computation of best possible solutions. Special attention is paid to multi-criteria tasks with competing cost and quality measures and the integration of simulation and optimization algorithms.
This includes consulting and structuring of decision processes, as well as the development and implementation of interactive decision support tools, especially for multi-objective optimization. We support the continuous process of an optimization problem by developing appropriate tools. Special attention is paid to the adequate choice of the model with respect to the quantity and quality of the available data. We use machine learning methods to process the data and to calibrate models, but also to augment models and to explain phenomena that cannot be modeled explicitly.