Kernelization algorithms are polynomial-time reductions from a problem to itself that guarantee their output to have a size not exceeding some bound. For example, d-Set Matching f...
Abstract. We obtain faster algorithms for problems such as rdimensional matching, r-set packing, graph packing, and graph edge packing when the size k of the solution is considered...
Michael R. Fellows, Christian Knauer, Naomi Nishim...
Abstract. We develop a generic framework for deriving linear-size problem kernels for NP-hard problems on planar graphs. We demonstrate the usefulness of our framework in several c...
Abstract. We consider the two-dimensional bin packing and strip packing problem, where a list of rectangles has to be packed into a minimal number of rectangular bins or a strip of...