A weighted full-Newton step primal-dual interior point algorithm for convex quadratic optimization
نویسندگان
چکیده
In this paper, a new weighted short-step primal-dual interior point algorithm for convex quadratic optimization (CQO) problems is presented. The algorithm uses at each interior point iteration only full-Newton steps and the strategy of the central path to obtain an ε-approximate solution of CQO. This algorithm yields the best currently wellknown theoretical iteration bound, namely, O( √ n log ε ) which is as good as the bound for the linear optimization analogue.
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تاریخ انتشار 2015