Many complex problems in practice can be reduced to constraint solving, which enables the use of highly optimized, standardized tools. However, recognizing the potential for applying constraint solving to a particular problem is not trivial. In addition, there are many aspects to consider when selecting suitable tools, as performance can be severely impaired by a suboptimal selection. In this course we deal with different applications that can benefit from constraint solving, strategies to reduce such applications to constraint solving problems and state-of-the art tools to solve such problems.
The lecture deals with the following contents:
The course aims to enable students to apply solutions based on constraint solving in practice. To this end, the course covers the following aspects:
In our beat your lecturer challenge, students develop their own solvers. On the DOMjudge-based platform, you can upload your solvers and pit them against the teaching team's solver and your fellow students' solvers on thousands of constraint solving instances. Beat the teaching team's solver for academic credit (Studienleistung) and your fellow students' solvers for glory (and small prizes).