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Trajectory-following methods for large-scale degenerate convex quadratic programming

Nick Gould(nick.gould***at***stfc.ac.uk)
Dominique Orban(dominique.orban***at***gerad.ca)
Daniel Robinson(daniel.p.robinson***at***jhu.edu)

Abstract: We consider a class of infeasible, path-following methods for convex quadratric programming. Our methods are designed to be effective for solving both nondegerate and degenerate problems, where degeneracy is understood to mean the failure of strict complementarity at a solution. Global convergence and a polynomial bound on the number of iterations required is given. An implementation, CQP, is available as part of GALAHAD. We illustrate the advantages of our approach on the CUTEr and Maros-Meszaros test sets.

Keywords: convex quadratic programming, degeneracy, infeasible interior-point method

Category 1: Nonlinear Optimization (Quadratic Programming )

Category 2: Optimization Software and Modeling Systems

Citation: Technical Report Rutherford Appleton Laboratory Chilton, Oxordshire OX110QX, England

Download: [PDF]

Entry Submitted: 09/02/2011
Entry Accepted: 09/02/2011
Entry Last Modified: 09/02/2011

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