A robust choice of the Lagrange multipliers in the successive quadratic programming method

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dc.contributor.advisorTapia, Richard A.en_US
dc.creatorCores-Carrera, Deboraen_US
dc.date.accessioned2009-06-04T00:27:19Zen_US
dc.date.available2009-06-04T00:27:19Zen_US
dc.date.issued1994en_US
dc.description.abstractWe study the choice of the Lagrange multipliers in the successive quadratic programming method (SQP) applied to the equality constrained optimization problem. It is known that the augmented Lagrangian SQP-Newton method depends on the penalty parameter only through the multiplier in the Hessian matrix of the Lagrangian function. This effectively reduces the augmented Lagrangian SQP-Newton method to the Lagrangian SQP Newton method where only the multiplier estimate depends on the penalty parameter. In this work, we construct a multiplier estimate that depends strongly on the penalty parameter and we derive a choice for the penalty parameter so that the Hessian matrix, restricted to the null space of the constraints, is positive definite and well conditioned. We demonstrate that the SQP-Newton method with this choice of Lagrange multipliers is locally and q-quadratically convergent.en_US
dc.format.extent69 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.callnoTHESIS MATH.SCI. 1994 CORESen_US
dc.identifier.citationCores-Carrera, Debora. "A robust choice of the Lagrange multipliers in the successive quadratic programming method." (1994) Diss., Rice University. <a href="https://hdl.handle.net/1911/16725">https://hdl.handle.net/1911/16725</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/16725en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectMathematicsen_US
dc.subjectOperations researchen_US
dc.titleA robust choice of the Lagrange multipliers in the successive quadratic programming methoden_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentMathematical Sciencesen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelDoctoralen_US
thesis.degree.nameDoctor of Philosophyen_US
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