Kernel-function based algorithms for semidefinitie optimization

Journal article (2009)
Department
Software Technology (EEMCS) (TU Delft)
Copyright: Roos, C.
DOI: https://doi.org/doi:10.1051/ro/2009011
Complexity Interior-point methods Semidefinite optimization Primal-dual method
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Published Date

01-06-2009

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Source:

RAIRO-Operations Research, 43, 2 (2009)

ISSN:

1290-3868

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Abstract

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 interiorpoint 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.

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