A Generalization of Nemhauser and Trotter's Local Optimization Theorem
Michael R. Fellows, Jiong Guo, Hannes Moser, Rolf Niedermeier

TL;DR
This paper extends the Nemhauser-Trotter theorem to vertex deletion and graph packing problems, introducing combinatorial algorithms and demonstrating a linear kernel for Bounded-Degree Deletion, with implications for biological network analysis.
Contribution
It generalizes the Nemhauser-Trotter theorem to new graph problems using combinatorial methods, providing kernelization results and complexity bounds.
Findings
Bounded-Degree Deletion admits a linear kernel for fixed d.
The framework applies to graph packing problems like star packing.
Bounded-Degree Deletion is W[2]-hard for unbounded d.
Abstract
The Nemhauser-Trotter local optimization theorem applies to the NP-hard Vertex Cover problem and has applications in approximation as well as parameterized algorithmics. We present a framework that generalizes Nemhauser and Trotter's result to vertex deletion and graph packing problems, introducing novel algorithmic strategies based on purely combinatorial arguments (not referring to linear programming as the Nemhauser-Trotter result originally did). We exhibit our framework using a generalization of Vertex Cover, called Bounded- Degree Deletion, that has promise to become an important tool in the analysis of gene and other biological networks. For some fixed d \geq 0, Bounded-Degree Deletion asks to delete as few vertices as possible from a graph in order to transform it into a graph with maximum vertex degree at most d. Vertex Cover is the special case of d = 0. Our generalization of…
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Taxonomy
TopicsAdvanced Graph Theory Research · Complexity and Algorithms in Graphs · Interconnection Networks and Systems
