Abstract
A recently developed method of reducing a minimal cut into a minimum cut solved a challenging generalization of the classical minimum cut problem. We show how to use this method in detail, along with a few solutions to (restricted version of) l-Bundled cut, l-chain SAT, and l-skew multicut. As many of the considered problems are NP-hard in general, we focus on parameterized complexity - solving them in f(l) ⋅ nᴼ⁽¹⁾ for some computable function f.