Issue |
RAIRO-Oper. Res.
Volume 43, Number 2, April-June 2009
|
|
---|---|---|
Page(s) | 189 - 199 | |
DOI | https://doi.org/10.1051/ro/2009011 | |
Published online | 28 April 2009 |
Kernel-function Based Algorithms for Semidefinite Optimization
1
Department of Informatics, University of Bergen,Post Box 7803 5020 Bergen, Norway;
melghami@ii.uib.no
2
Department of Mathematics, Shanghai University, Shanghai, 200444,
P.R. China; yqbai@shu.edu.cn
3
Faculty of Electrical Engineering, Mathematics, and Computer
Science, Delft University of Technology, P.O. Box 5031, 2600 GA
Delft, The Netherlands;
C.Roos@ewi.tudelft.nl
Received:
10
October
2007
Accepted:
27
January
2009
Recently, Y.Q. Bai, M. El Ghami and C. Roos [3] introduced a new class of so-called eligible kernel functions which are defined by some simple conditions. The authors designed primal-dual interior-point methods for linear optimization (LO) based on eligible kernel functions and simplified the analysis of these methods considerably. In this paper we consider the semidefinite optimization (SDO) problem and we generalize the aforementioned results for LO to SDO. The iteration bounds obtained are analogous to the results in [3] for LO.
Mathematics Subject Classification: 90C22 / 90C31
Key words: Semidefinite optimization / interior-point methods / primal-dual method / complexity.
© EDP Sciences, ROADEF, SMAI, 2009
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