Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/111500
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dc.contributor.authorWagner, M.-
dc.contributor.authorFriedrich, T.-
dc.contributor.authorLindauer, M.-
dc.date.issued2017-
dc.identifier.citationProceedings of the Institution of Civil Engineers: Civil Engineering, 2017, pp.1704-1711-
dc.identifier.isbn9781509046027-
dc.identifier.issn0965-089X-
dc.identifier.urihttp://hdl.handle.net/2440/111500-
dc.description.abstractFor 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.-
dc.description.statementofresponsibilityMarkus Wagner, Tobias Friedrich and Marius Lindauer-
dc.language.isoen-
dc.publisherIEEE-
dc.relation.ispartofseriesIEEE Congress on Evolutionary Computation-
dc.rights©2017 IEEE-
dc.source.urihttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7959755-
dc.titleImproving local search in a minimum vertex cover solver for classes of networks-
dc.typeConference paper-
dc.contributor.conferenceIEEE Congress on Evolutionary Computation (CEC 2017) (5 Jun 2017 - 8 Jun 2017 : San Sebastián, SPAIN)-
dc.identifier.doi10.1109/CEC.2017.7969507-
dc.relation.granthttp://purl.org/au-research/grants/arc/DE160100850-
pubs.publication-statusPublished-
dc.identifier.orcidWagner, M. [0000-0002-3124-0061]-
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