Polynomial Kernelizations for MIN F^+Pi_1 and MAX NP

Stefan Kratsch
The relation of constant-factor approximability to fixed-parameter tractability and kernelization is a long-standing open question. We prove that two large classes of constant-factor approximable problems, namely~$\textsc{MIN F}^+\Pi_1$ and~$\textsc{MAX NP}$, including the well-known subclass~$\textsc{MAX SNP}$, admit polynomial kernelizations for their natural decision versions. This extends results of Cai and Chen (JCSS 1997), stating that the standard parameterizations of problems in~$\textsc{MAX SNP}$ and~$\textsc{MIN F}^+\Pi_1$ are fixed-parameter tractable, and complements recent research on problems that do not admit...
This data center is not currently reporting usage information. For information on how your repository can submit usage information, please see our documentation.
We found no citations for this text. For information on how to provide citation information, please see our documentation.