Parameterized Capacitated Vertex Cover Revisited
Michael Lampis, Manolis Vasilakis

TL;DR
This paper analyzes the computational complexity of the Capacitated Vertex Cover problem across various parameters, establishing tight bounds and optimal algorithms under ETH and other complexity assumptions.
Contribution
It provides a fine-grained parameterized complexity analysis, proving optimality of existing algorithms and barriers for improvements for multiple structural parameters.
Findings
No $k^{o(k)} n^{O(1)}$ algorithm exists under ETH for parameter $k$.
Improved algorithms for vertex integrity with running time $ ext{vi}^{O( ext{vi}^2)} n^{O(1)}$.
Capacitated Vertex Cover remains NP-hard on graphs with clique-width 6.
Abstract
Capacitated Vertex Cover is the hard-capacitated variant of Vertex Cover: given a graph, a capacity for every vertex, and an integer , the task is to select at most vertices that cover all edges and assign each edge to one of its chosen endpoints so that no chosen vertex receives more incident edges than its capacity. This problem is a classical benchmark in parameterized complexity, as it was among the first natural problems shown to be W[1]-hard when parameterized by treewidth. We revisit its exact complexity from a fine-grained parameterized perspective and obtain a much sharper picture for several standard parameters. For the natural parameter , we prove under the Exponential Time Hypothesis (ETH) that no algorithm with running time exists. In particular, this shows that the known algorithms with running time $k^{\mathcal{O}(\mathrm{tw})}…
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