A Simple quadratically convergent Interior Point Algorithm for Linear Programming and Convex quadratic Programming

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dc.contributor.authorTits, A.L.en_US
dc.contributor.authorZhou, J.L.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T09:54:10Z
dc.date.available2007-05-23T09:54:10Z
dc.date.issued1993en_US
dc.description.abstractAn algorithm for linear programming (LP) and convex quadratic programming (CQP) is proposed, based on an interior point iteration introduced more than ten years ago by J. Herskovits for the solution of nonlinear programming problems. Herskovits' iteration can be simplified significantly in the LP/CQP case, and quadratic convergence from any initial point can be achieved. Interestingly the resulting algorithm is closely related to a popular scheme, proposed in 1989 by Kojima et al. independently of Herskovits' work.en_US
dc.format.extent790138 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/5398
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1993-53en_US
dc.subjectlinear programmingen_US
dc.subjectquadratic programmingen_US
dc.subjectglobal convergenceen_US
dc.subjectquadratic convergenceen_US
dc.subjectIntelligent Servomechanismsen_US
dc.titleA Simple quadratically convergent Interior Point Algorithm for Linear Programming and Convex quadratic Programmingen_US
dc.typeTechnical Reporten_US

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