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In addition, the return mapping algorithm is built in negative normal convex cone of violated constraints of level sets to conveniently give an initial structure with multi-constraints, multi-materials and non-design domains.

在这些研究的基础上,提出了适用于一般目标函数、多材料、多约束和多载荷工况的结构拓扑优化的水平集算法4.1,并给出了刚性结构、柔性机构和复合材料微结构设计算法5.1、6.1和7.1,以及大量的数值算例。

This paper is a discussion of new algorithm for convex objective function and convex programming with constraints.The algorithm is an extension and improvement for a new linear programming.

对一般凸目标函数和一般凸集约束的凸规划问题新解法进行探讨,它是线性规划一种新算法的扩展和改进。

This algorithm is proposed on the basis of the thought as follovvs: as for three dimensional Euclid space, the feasible region of any linear programming problem is a extended convex polyhedron, of which surface is consisted of some planes, and its objective function can be regarded as a parallel plane pencil with objective function value acting as parameter.

如果线性规划问题有最优解,那么过可行域的一已知顶点必至少存在这样一条棱——它以该己知顶点为一端点,可行域的另一顶点为另一端点,并使目标函数在另一端点的函数值优于己知端点的函数值,否则,该己知点就是线性规划问题的最优解。

This can be viewed as a particular case of nonlinear programming or as generalization of linear or convex quadratic programming.

非线性规划研究的一般情况下,目标函数或限制或都包含非线性部分。

The method of convex quadratic programming relaxation has been used for the scheduling with rejection .

用凸二次规划松弛方法研究工件具有就绪时间,目标函数为工件总拒绝费用与接受工件的带权总完工时间之和的工件可拒绝排序问题,得到界为2的多项式时间近似算法。

Convex programming studies the case when the objective function is convex and the constraints, if any, form a convex set.

二次规划的目标函数可以有二次条件,而设置必须指定与线性等式和不等式。

By weakening the premise of the convexity of the objective function required in paper[7], we prove the sufficient desent property and the global convergence with the strong Wolfe line search.

在第二章中,我们参照文献[7]中的方法,提出了一类与HS算法相关的共轭梯度算法,并减弱了文[7]中要求目标函数二阶连续可微且为凸的前提条件,采用强Wolfe线搜索,在较弱的条件下证明了这一类算法具有充分下降性和全局收敛性。

Taking the unknown coordinate in curved surface and curve as design variables, the equation of curved surface as constrained condition, and the distance between unknown coordinate as objective function, optimization is proposed to minimize the distance between curved surface and curve.

建立以曲面、曲线上未知,点坐标设计变量,以曲面和曲线方程为约束条件,以曲线和曲面距离为目标函数的约束优化方法来精确地确定曲面和曲线之间最短距离,同时确定获得最短距离对应的坐标点。

With the constraints of these feature points, perspective projection, coplanarity and colinearity, the curved surfaces can be recovered by minimizing the linearly constrained quadric objective function.

把特征点的位置、共面、共线、透视投影等作为约束,通过最小化线性约束下的二次目标函数实现曲面重建。

This method includes fixed cost in generation and transmission cost optimization function and a quadratic programming model is proposed.

该方法在目标函数中考虑了电网的固定成本,形成了以系统发、输电费用最小为优化条件的二次规划模型。

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