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。
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。
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。
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。
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。
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。
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。
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。
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。
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。
To the nonconvex programming, the article makes it local convexification by introducing a simple penalty function into the objective function, and solves it like solving convex programming.
针对非凸规划，本文引进一简单的惩罚函数将其局部凸化，然后用凸规划的方法求解。
Convex function plays an important role in mathematical programming.
凸函数在数学规划中具有十分重要的作用。
Some numerical results for a large number of random convex quadratic programming problems show that the new algorithm is efficient and might be a polynomial-time algorithm under some conditions.
大量的关于随机的凸二次规划问题的数值实验结果表明它的计算效率是高的，在某些条件下可能是多项式时间算法。
SVM transforms machine learning to solve an optimization problem, and to solve a convex quadratic programming problem by the optimization theory and method constructing algorithms.
它将机器学习问题转化为求解最优化问题，并应用最优化理论构造算法来解决凸二次规划问题。
This paper deals with the nonlinear equations algorithm for convex nonlinear programming problems with equality constraints.
对等式约束的凸非线性规划问题的非线性方程组算法进行了研究。
Assuming knowledge of extreme points, we develop bounds for associated convex combinations and improve bounds on the integer programming problems objective function and variables.
应用已有的极点理论，优化相伴凸组合的界并改进整数规划问题的目标函数及变量的界。
Finally, optimality necessary and sufficient conditions for nonlinear convex semidefinite programming are proved.
并给出了非线性半定规划的最优性必要和充分条件。
Furthermore, it gives an optimum condition and a simple algorithm of the special interaction programming by changing it into a special convex quadratic bilevel programming.
并且通过把该交叉规划转化为特殊的凸二次双水平规划，给出这类交叉规划的最优性条件和求解算法。
Based on the convex simplex method for nonlinear programming, a sensitivity analysis of consumption coefficient matrix in linear fractional programming is presented.
基于解非线形规划的凸单纯形法，对一类线形分式规划的消耗系数矩阵进行灵敏度分析。
Lower approximation algorithm and its solve of convex quadratic programming are also given in this article.
混合优化控制算法，给出了求解最优控制器的上逼近算法及其凸二次规划求解方法。
In this paper it is improved appropriately and applied to the convex integer programming problems.
本文对其做适当改进，用于解凸整数规划问题。
The problem of collision detection between a pair of convex objects is summed up a problem of non-linear programming with restrict conditions in this paper.
将两凸物体间碰撞检测问题归结为一个带约束条件的非线性规划问题。
The inclusion-constrained programming and the cone-constrained programming are connected in this paper by the property "a set-valued map with convex graph";
通过引入“集值映射具有凸图”这一性质，将包含约束凸规划与锥约束规划联系了起来；
In the fifth chapter, we introduce an Augmented Lagrangian method for solving convex Nonlinear Semidefinite Programming (NLSDP) problems.
第五章，给出了解凸非线性半定规划的一种广义拉格朗日算法。
In this paper, the stability of proper efficient solution of multi-objective convex parametric programming is discussed.
本文讨论多目标凸参数规划的真有效解稳定性。
Based on dual relaxation method to extend a special convex separable programming algorithm, this tracking algorithm was constructed by parametric analysis.
该参数优化算法可在对偶松弛凸可分规划算法的主循环之外，通过少量参数化扩展得到。
Researches on bundle methods touch upon such mathematical branches as convex analysis, nonlinear programming and nonsmooth analysis.
对束方法的研究涉及凸分析，线性和非线性规划，非光滑分析等数学分支。
The duality conditions for multiobjective semi-infinite programming with semilocally convex functions are given.
研究半局部凸函数在多目标半无限规划下的对偶性。
The duality conditions for multiobjective semi-infinite programming with semilocally convex functions are given.
研究半局部凸函数在多目标半无限规划下的对偶性。
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