Bounds on Eigenvalues of Matrices Arising from Interior-Point Methods

Interior-point methods feature prominently among numerical methods for inequality-constrained optimization problems, and involve the need to solve a sequence of linear systems that typically become increasingly ill-conditioned with the iterations. To solve these systems, whose original form has a no...

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Bibliographic Details
Published in:SIAM journal on optimization 2014-01, Vol.24 (1), p.49-83
Main Authors: Greif, Chen, Moulding, Erin, Orban, Dominique
Format: Article
Language:English
Subjects:
Applied mathematics
Eigenvalues
Linear programming
Numerical analysis
Optimization
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Summary:Interior-point methods feature prominently among numerical methods for inequality-constrained optimization problems, and involve the need to solve a sequence of linear systems that typically become increasingly ill-conditioned with the iterations. To solve these systems, whose original form has a nonsymmetric $3\times 3$ block structure, it is common practice to perform block elimination and either solve the resulting reduced saddle-point system, or further reduce the system to the Schur complement and apply a symmetric positive definite solver. In this paper we use energy estimates to obtain bounds on the eigenvalues of the matrices, and conclude that the original unreduced matrix has more favorable eigenvalue bounds than the alternative reduced versions. Our analysis includes regularized variants of those matrices that do not require typical regularity assumptions. [PUBLICATION ABSTRACT]
ISSN:1052-6234
1095-7189
DOI:10.1137/120890600