Improving local search in a minimum vertex cover solver for classes of networks

authored by

Markus Wagner, Tobias Friedrich, Marius Lindauer

Abstract

For the minimum vertex cover problem, a wide range of solvers has been proposed over the years. Most classical exact approaches are encountering run time issues on massive graphs that are considered nowadays. A straightforward alternative approach is then to use heuristics, which make assumptions about the structure of the studied graphs. These assumptions are typically hard-coded and are hoped to work well for a wide range of networks - which is in conflict with the nature of broad benchmark sets. With this article, we contribute in two ways. First, we identify a component in an existing solver that influences its performance depending on the class of graphs, and we then customize instances of this solver for different classes of graphs. Second, we create the first algorithm portfolio for the minimum vertex cover to further improve the performance of a single integrated approach to the minimum vertex cover problem.

External Organisation(s)

University of Adelaide
University of Freiburg
University of Potsdam

Type

Conference contribution

Pages

1704-1711

No. of pages

8

Publication date

07.07.2017

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Artificial Intelligence, Computer Networks and Communications, Computer Science Applications, Signal Processing

Electronic version(s)

https://doi.org/10.1109/cec.2017.7969507 (Access: Closed)