An iterative working-set method for large-scale nonconvex quadratic programming

DOI10.1016/S0168-9274(02)00120-4zbMath1012.65054OpenAlexW2131687653WikidataQ58185834 ScholiaQ58185834MaRDI QIDQ1862010

Nicholas I. M. Gould, Phillipe L. Toint

Publication date: 10 March 2003

Published in: Applied Numerical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0168-9274(02)00120-4

zbMATH Keywords

quadratic programmingpreconditioningconjugate gradient methodnonconvexLanczos methodslarge-scaleactive-set methodFortran 90 package QPAGALAHAD library

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Quadratic programming (90C20) Iterative numerical methods for linear systems (65F10) Numerical computation of matrix norms, conditioning, scaling (65F35) Methods of reduced gradient type (90C52)

Related Items

Primal and dual active-set methods for convex quadratic programming, An SR1/BFGS SQP algorithm for nonconvex nonlinear programs with block-diagonal Hessian matrix, Global optimization of truss topology with discrete bar areas. I: Theory of relaxed problems, Adaptive tetrahedral meshing in free-surface flow, QPLIB: a library of quadratic programming instances, QPA, An Active-Set Method for Quadratic Programming Based On Sequential Hot-Starts, A globally convergent primal-dual active-set framework for large-scale convex quadratic optimization, Methods for convex and general quadratic programming

Uses Software

• HSL
• MA57
• QP
• heapsort
• HSL-VF05

Cites Work

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