On Efficient Semidefinite Relaxations for Quadratically Constrained Quadratic Programming

dc.comment.hiddenThe deadline is May21th, I hope to get acceptance as soon as possible. Thanks!en
dc.contributor.authorDing, Yichuan
dc.date.accessioned2007-05-18T13:39:47Z
dc.date.available2007-05-18T13:39:47Z
dc.date.issued2007-05-18T13:39:47Z
dc.date.submitted2007-05-17
dc.description.abstractTwo important topics in the study of Quadratically Constrained Quadratic Programming (QCQP) are how to exactly solve a QCQP with few constraints in polynomial time and how to find an inexpensive and strong relaxation bound for a QCQP with many constraints. In this thesis, we first review some important results on QCQP, like the S-Procedure, and the strength of Lagrangian Relaxation and the semidefinite relaxation. Then we focus on two special classes of QCQP, whose objective and constraint functions take the form trace(X^TQX + 2C^T X) + β, and trace(X^TQX + XPX^T + 2C^T X)+ β respectively, where X is an n by r real matrix. For each class of problems, we proposed different semidefinite relaxation formulations and compared their strength. The theoretical results obtained in this thesis have found interesting applications, e.g., solving the Quadratic Assignment Problem.en
dc.format.extent477363 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/10012/3044
dc.language.isoenen
dc.pendingfalseen
dc.publisherUniversity of Waterlooen
dc.subjectSemidefinite Programmingen
dc.subjectQuadratically Constrained Quadratic Programmingen
dc.subjectQuadratic Matrix Programmingen
dc.subjectQuadratic Assignment Problemen
dc.subject.programCombinatorics and Optimizationen
dc.titleOn Efficient Semidefinite Relaxations for Quadratically Constrained Quadratic Programmingen
dc.typeMaster Thesisen
uws-etd.degreeMaster of Mathematicsen
uws-etd.degree.departmentCombinatorics and Optimizationen
uws.peerReviewStatusUnrevieweden
uws.scholarLevelGraduateen
uws.typeOfResourceTexten

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