Backbones in Optimization and Approximation

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dc.contributor.authorSlaney, John K
dc.contributor.authorWalsh, Toby
dc.coverage.spatialSeattle USA
dc.date.accessioned2015-12-10T23:23:22Z
dc.date.available2015-12-10T23:23:22Z
dc.date.createdJuly 4 2001
dc.date.issued2001
dc.date.updated2016-02-24T09:47:02Z
dc.description.abstractWe study the impact of backbones in optimization and approximation problems. We show that some optimization problems like graph coloring resemble decision problems, with problem hardness positively correlated with backbone size. For other optimization pro
dc.identifier.isbn1558607773
dc.identifier.urihttp://hdl.handle.net/1885/66932
dc.publisherMorgan Kauffman Publishers
dc.relation.ispartofseriesInternational Joint Conference on Artificial Intelligence (IJCAI 2001)
dc.sourceIJCAI-01: Proceedings of the 17th International Joint Conference on Artificial Intelligence
dc.subjectKeywords: Approximate solution; Approximation problems; Decision problems; Graph colorings; Number partitioning; Optimization problems; Problem hardness; Traveling salesperson problem; Artificial intelligence; Hardness; Optimization
dc.titleBackbones in Optimization and Approximation
dc.typeConference paper
local.bibliographicCitation.lastpage259
local.bibliographicCitation.startpage254
local.contributor.affiliationSlaney, John K, College of Engineering and Computer Science, ANU
local.contributor.affiliationWalsh, Toby, University of York
local.contributor.authoremailu8800435@anu.edu.au
local.contributor.authoruidSlaney, John K, u8800435
local.description.notesImported from ARIES
local.description.refereedYes
local.identifier.absfor010303 - Optimisation
local.identifier.ariespublicationMigratedxPub1370
local.identifier.scopusID2-s2.0-84880914510
local.identifier.uidSubmittedByMigrated
local.type.statusPublished Version

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