A major aim of the Research Campus MODAL is the development and use of mathematical synergies between the individual labs of the network. In this context, the fields of discrete, continuous and stochastic optimization are to be cross-linked to a larger extent. This corresponds to the requirements of everyday practice, where these aspects usually occur simultaneously. The research campus explores relevant application cases and offers the opportunity to jointly develop and transfer approaches, standards, data pools, methods, and software. Industrial partners from various sectors can cooperate more easily than with their direct competitors. A starting point for an integration of this type is the development of methods for the solution of a general class of discrete-stochastic optimization problems. In a first step, we plan to develop methods of general, integer, discrete-stochastic Constraint Programming (CIP) and their linkage to commonly used CIP solvers, in this case the SCIP framework developed at ZIB, in order create a powerful standard tool.

Currently, the work of the members of SynLab focuses on the following topics:

SL-1: Extended Mathematical Programming
Lead: Dr. Stefan Vigerske

SL-2: Solver technology for mixed-integer nonlinear programming
Lead: Dr. Ambros Gleixner and Dr. Stefan Vigerske

SL-3: Decomposition techniques
Lead: Dr. Stephen J. Maher

SL-4: High Throughput Optimization & Software as a Service
Lead: Prof. Dr. Thorsten Koch

SL-5: Cutting planes and outer-approximation
Lead: Dr. Tobias Achterberg and Dr. Ambros Gleixner

SL-6: Branching and conflict analysis
Lead: Dr. Timo Berthold

SL-7: Parallel algorithms
Lead: Dr. Stephen J. Maher and Dr. Yuji Shinano

SL-8: swMATH
Lead: Wolfgang Dalitz