Kernel-function Based Algorithms for Semidefinite Optimization
نویسندگان
چکیده
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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عنوان ژورنال:
- RAIRO - Operations Research
دوره 43 شماره
صفحات -
تاریخ انتشار 2009