A 0.821-Ratio Purely Combinatorial Algorithm for Maximum k-vertex Cover in Bipartite Graphs
A 0.821-Ratio Purely Combinatorial Algorithm for Maximum k-vertex Cover in Bipartite Graphs
Our goal in this paper is to propose a \textit{combinatorial algorithm} that beats the only such algorithm known previously, the greedy one. We study the polynomial approximation of the Maximum Vertex Cover Problem in bipartite graphs by a purely combinatorial algorithm and present a computer assisted analysis of it, that finds the worst case approximation guarantee that is bounded below by~0.821.
25 pages, 2 figures
- Panthéon-Assas University France
- University of Paris France
- Lamsade France
- Sorbonne Paris Cité France
- Centre national de la recherche scientifique France
FOS: Computer and information sciences, Greedy approaches, Vertex Cover problems, Combinatorial mathematics, Polynomial approximation, Computer-assisted analysis, QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány, information science, [INFO] Computer Science [cs], Approximation algorithms, Graph theory, Vertex cover, Computer Science - Data Structures and Algorithms, Combinatorial algorithm, Data Structures and Algorithms (cs.DS), Computer Aided Analysis, Algorithms, Polynomial time approximation, Bipartite graphs
FOS: Computer and information sciences, Greedy approaches, Vertex Cover problems, Combinatorial mathematics, Polynomial approximation, Computer-assisted analysis, QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány, information science, [INFO] Computer Science [cs], Approximation algorithms, Graph theory, Vertex cover, Computer Science - Data Structures and Algorithms, Combinatorial algorithm, Data Structures and Algorithms (cs.DS), Computer Aided Analysis, Algorithms, Polynomial time approximation, Bipartite graphs
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).1 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!