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Complexity analysis and numerical implementation of primal-dual interior-point methods for convex quadratic optimization based on a finite barrier.
- Source :
-
Numerical Algorithms . Feb2013, Vol. 62 Issue 2, p289-306. 18p. - Publication Year :
- 2013
-
Abstract
- In this paper, we present primal-dual interior-point methods for convex quadratic optimization based on a finite barrier, which has been investigated earlier for the case of linear optimization by Bai et al. (SIAM J Optim 13(3):766-782, ). By means of the feature of the finite kernel function, we study the complexity analysis of primal-dual interior-point methods based on the finite barrier and derive the iteration bounds that match the currently best known iteration bounds for large- and small-update methods, namely, $O(\sqrt{n}\log{n}\log{\frac{n}{\varepsilon}})$ and $O(\sqrt{n}\log{\frac{n}{\varepsilon}})$, respectively, which are as good as the linear optimization analogue. Numerical tests demonstrate the behavior of the algorithms with different parameters. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10171398
- Volume :
- 62
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Numerical Algorithms
- Publication Type :
- Academic Journal
- Accession number :
- 85139163
- Full Text :
- https://doi.org/10.1007/s11075-012-9581-y