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A Polynomial-time Interior-point Algorithm for Convex Quadratic Semidefinite Optimization

Y. Q. BaiF. Y. WangX. W. Luo — 2010

RAIRO - Operations Research

In this paper we propose a primal-dual interior-point algorithm for convex quadratic semidefinite optimization problem. The search direction of algorithm is defined in terms of a matrix function and the iteration is generated by full-Newton step. Furthermore, we derive the iteration bound for the algorithm with small-update method, namely, ( n log n ε ), which is best-known bound so far.

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