In this thesis algorithms for quadratic programming problems are researched.

本文主要研究了二次规划问题的求解算法.

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This paper introduces a feasible direction method for solving high - dimensional convex quadratic programming.

介绍一种求解高维凸二次规划的可行方向法.

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Hence incremental power and reactive power of generators were computed from this quadratic programming model.

求解这个二次规划模型得到发电机有功和无功功率增量.

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This method is easier than quadratic programming , but it is sensitive to the noise and outliers.

但是按照这样的方法所得到的结果对噪声和离群数据十分敏感.

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The current sequential quadratic programming ( SQP ) type algorithm may fail if the QP subproblem is infeasible.

序列二次规划方法 ( SQP ) 是解决非线性规划问题最有效的算法之一,但是当QP子问题不可行时算法可能会失败.

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In this paper, a new algorithm for a kind of convex quadratic programming is introduced.

本文给出了求解一类凸二次规划问题的新算法.

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