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The BPMPD interior point solver for convex quadratic problems*

The BPMPD interior point solver for convex quadratic problems* The paper describes the convex quadratic solver BPMPD Version 2.21. The solver is based on the infeasible–primal–dual algorithm extended by the predictor–corrector and target–following techniques. The discussion includes topics related to the implemented algorithm and numerical algebra employed. We outline the presolve, scaling and starting point stategies used in BPMPD, and special attention is given for sparsity and stability issues. Computational results are given on a demonstrative set of convex quadratic problems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Optimization Methods and Software Taylor & Francis

The BPMPD interior point solver for convex quadratic problems*

Optimization Methods and Software , Volume 11 (1-4): 19 – Jan 1, 1999
19 pages

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References (27)

Publisher
Taylor & Francis
Copyright
Copyright Taylor & Francis Group, LLC
ISSN
1029-4937
eISSN
1055-6788
DOI
10.1080/10556789908805758
Publisher site
See Article on Publisher Site

Abstract

The paper describes the convex quadratic solver BPMPD Version 2.21. The solver is based on the infeasible–primal–dual algorithm extended by the predictor–corrector and target–following techniques. The discussion includes topics related to the implemented algorithm and numerical algebra employed. We outline the presolve, scaling and starting point stategies used in BPMPD, and special attention is given for sparsity and stability issues. Computational results are given on a demonstrative set of convex quadratic problems.

Journal

Optimization Methods and SoftwareTaylor & Francis

Published: Jan 1, 1999

Keywords: Constrained optimization; interior point methods

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