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The Technische Universitat Munchen has been a FICO Academic Partner since 2005, using the FICO Xpress Optimization Suite in teaching and research – including the work of optimizing the model for this award-winning project.
"The problem of land consolidation is emotionally very rewarding, as it helps individual farmers and entire rural regions to survive economically," said Peter Gritzmann, "But it is also mathematically exciting, since it is extremely challenging and requires deep new mathematics and algorithms. Additionally, this research paves the way for fascinating new applications in the analysis of Big Data. Naturally, the mathematical models and ideas could not be brought into the reality without an extremely powerful optimization workhorse like FICO Xpress."
Professors Brieden and Gritzmann have already successfully developed extended and specifically customized models for several problem areas, including insurance loss prediction, maintenance prediction, and shipping logistics. The foundations of their algorithms are deep geometric insights that lead to high-quality segmentation of big data. Part of what makes their work particularly interesting for practitioners is the fact that it is a non-black-box algorithm which works with small setup costs and has high predictive power.