  Handling symmetries in optimization problems is essential for devising
efficient solution methods. In this article, we present a general framework
that captures many of the already existing symmetry handling methods. While
these methods are mostly discussed independently from each other, our framework
allows to apply different methods simultaneously and thus outperforming their
individual effect. Moreover, most existing symmetry handling methods only apply
to binary variables. Our framework allows to easily generalize these methods to
general variable types. Numerical experiments confirm that our novel framework
is superior to the state-of-the-art symmetry handling methods as implemented in
the solver SCIP on a broad set of instances.
