A Matrix-Free Trust-Region SQP Method for Equality Constrained Optimization

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dc.citation.firstpage1507
dc.citation.issueNumber3
dc.citation.journalTitleSIAM Journal on Optimization
dc.citation.lastpage1541
dc.citation.volumeNumber24
dc.contributor.authorHeinkenschloss, Matthias
dc.contributor.authorRidzal, Denis
dc.date.accessioned2016-02-02T21:22:53Z
dc.date.available2016-02-02T21:22:53Z
dc.date.issued2014
dc.description.abstractWe develop and analyze a trust-region sequential quadratic programming (SQP) method for the solution of smooth equality constrained optimization problems, which allows the inexact and hence iterative solution of linear systems. Iterative solution of linear systems is important in large-scale applications, such as optimization problems with partial differential equation constraints, where direct solves are either too expensive or not applicable. Our trust-region SQP algorithm is based on a composite-step approach that decouples the step into a quasi-normal and a tangential step. The algorithm includes critical modifications of substep computations needed to cope with the inexact solution of linear systems. The global convergence of our algorithm is guaranteed under rather general conditions on the substeps. We propose algorithms to compute the substeps and prove that these algorithms satisfy global convergence conditions. All components of the resulting algorithm are specified in such a way that they can be directly implemented. Numerical results indicate that our algorithm converges even for very coarse linear system solves.
dc.identifier.citationHeinkenschloss, Matthias and Ridzal, Denis. "A Matrix-Free Trust-Region SQP Method for Equality Constrained Optimization." <i>SIAM Journal on Optimization,</i> 24, no. 3 (2014) SIAM: 1507-1541. http://dx.doi.org/10.1137/130921738.
dc.identifier.doihttp://dx.doi.org/10.1137/130921738
dc.identifier.urihttps://hdl.handle.net/1911/88308
dc.language.isoeng
dc.publisherSIAM
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
dc.subject.keywordsequential quadratic programming
dc.subject.keywordtrust-region
dc.subject.keywordlarge-scale optimization
dc.subject.keywordmatrix free
dc.subject.keywordinexact linear system solvers
dc.subject.keywordPDE-constrained optimization
dc.subject.keywordKrylov subspace methods
dc.titleA Matrix-Free Trust-Region SQP Method for Equality Constrained Optimization
dc.typeJournal article
dc.type.dcmiText
dc.type.publicationpublisher version
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