Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.205
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dc.contributor.authorJansson, Christian-
dc.contributor.authorKeil, Christian-
dc.date.accessioned2006-03-15T17:07:30Zde_DE
dc.date.available2006-03-15T17:07:30Zde_DE
dc.date.issued2005-
dc.identifier.urihttp://tubdok.tub.tuhh.de/handle/11420/207-
dc.description.abstractA wide variety of problems in global optimization, combinatorial optimization as well as systems and control theory can be solved by using linear and semidefinite programming. Sometimes, due to the use of floating point arithmetic in combination with ill-conditioning and degeneracy, erroneous results may be produced. The purpose of this article is to show how rigorous error bounds for the optimal value can be computed by carefully postprocessing the output of a linear or semidefinite programming solver. It turns out that in many cases the computational costs for postprocessing are small compared to the effort required by the solver. Numerical results are presented including problems from the SDPLIB and the NETLIB LP library; these libraries contain many ill-conditioned and real life problems.en
dc.language.isoende_DE
dc.rightsinfo:eu-repo/semantics/openAccess-
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectsemidefinite programmingde_DE
dc.subjectglobal optimizationde_DE
dc.subjectcombinatorial optimizationde_DE
dc.titleRigorous error bounds for the optimal value in semidefinite programmingde_DE
dc.typeWorking Paperde_DE
dc.date.updated2006-03-15T17:07:31Zde_DE
dc.identifier.urnurn:nbn:de:gbv:830-opus-2700de_DE
dc.identifier.doi10.15480/882.205-
dc.type.diniworkingPaper-
dc.subject.gndSemidefinite Optimierungde
dc.subject.gndKombinatorische Optimierungde
dc.subject.gndGlobale Optimierungde
dc.subject.ddccode510-
dcterms.DCMITypeText-
tuhh.identifier.urnurn:nbn:de:gbv:830-opus-2700de_DE
tuhh.publikation.typworkingPaperde_DE
tuhh.opus.id270de_DE
tuhh.oai.showtruede_DE
dc.identifier.hdl11420/207-
tuhh.abstract.englishA wide variety of problems in global optimization, combinatorial optimization as well as systems and control theory can be solved by using linear and semidefinite programming. Sometimes, due to the use of floating point arithmetic in combination with ill-conditioning and degeneracy, erroneous results may be produced. The purpose of this article is to show how rigorous error bounds for the optimal value can be computed by carefully postprocessing the output of a linear or semidefinite programming solver. It turns out that in many cases the computational costs for postprocessing are small compared to the effort required by the solver. Numerical results are presented including problems from the SDPLIB and the NETLIB LP library; these libraries contain many ill-conditioned and real life problems.de_DE
tuhh.publication.instituteZuverlässiges Rechnen E-19de_DE
tuhh.identifier.doi10.15480/882.205-
tuhh.type.opusResearchPaper-
tuhh.institute.germanZuverlässiges Rechnen E-19de
tuhh.institute.englishReliable Computing E-19en
tuhh.institute.id38de_DE
tuhh.type.id17de_DE
tuhh.gvk.hasppnfalse-
dc.type.driverworkingPaper-
dc.identifier.oclc930768022-
dc.type.casraiWorking Paper-
item.languageiso639-1en-
item.fulltextWith Fulltext-
item.openairetypeWorking Paper-
item.grantfulltextopen-
item.creatorOrcidJansson, Christian-
item.creatorOrcidKeil, Christian-
item.openairecristypehttp://purl.org/coar/resource_type/c_8042-
item.creatorGNDJansson, Christian-
item.creatorGNDKeil, Christian-
item.cerifentitytypePublications-
crisitem.author.deptZuverlässiges Rechnen E-19-
crisitem.author.deptZuverlässiges Rechnen E-19-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
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