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1·Objective: To search optimal solutions of convex programming problems with linear constraints.

求线性约束凸规划问题的最优解。

2·The key idea of SSVM is to transform the standard model of SVM into an unconstraint quadric convex programming problem.

SSVM模型的基本思想是将标准的支撑向量机模型转化成一个无约束二次凸规划模型进行求解。

3·The paper offers a dual problem for the semi-infinite convex programming by using the directional derivative with zero dual gap.

本文对半无限凸规划提出一个用方向导数表述的对偶问题，其对偶间隙为零。

4·AimTo construct the simple and feasible neural networks for solving a class of linearly constrained convex programming problems.

目的建立求解一类线性约束非线性凸规划的简单可行的神经网络。

5·In this paper, they modify the CHIP method and use the modified one to solve a broader class of non-convex programming problems.

文中对CHIP方法进行了改进并利用改进的方法去求解更大一类的非凸规划问题。

6·Finally, the relationships between generalized set-valued variational inclusion problems and non-convex programming are studied.

最后研究了广义集值变分包含问题与非凸规划之间的关系。

7·In convex programming theory, a constrained optimization problem, by KT conditions, is usually converted into a mixed nonlinear complementarity problem.

在凸规划理论中，通过KT条件，往往将约束最优化问题归结为一个混合互补问题来求解。

8·In the branch and bound method for solving non-convex programming, the choice of region subdivision directly affects the convergence of the whole algorithm.

在求解非凸规划的分枝定界法中，剖分区间的选取直接影响到整个算法的收敛速度。

9·Based on the dual relaxation method, an extended convex programming and sequential linear programming optimal power flow approach is presented for online optimal dispatch.

提出了一种基于对偶松弛法的扩展凸规划和序列线性规划相结合的在线最优潮流方法。

10·The optimization problem can be solved based on the density-stiffness interpolation scheme and the method of moving asymptotes belonging to sequential convex programming approaches.

采用基于密度刚度插值模型和序列凸规划法中的移动渐近线方法求解优化模型。 通过经典算例验证了本方法的有效性。