The problem is changed to solving the linear inequality group with two unknown, thus, we can get the optimal solution by the computer.
从而使问题转化成求解二元线性不等式组的问题，为此可方便地借助计算机求出最佳结果。
We propose a new trust region algorithm for special linear inequality constrained optimization problems with nonnegative bound constraints.
对一类带有非负边界约束的线性不等式约束优化问题进行了研究，提出了一种新的信赖域算法。
We present an affine scaling trust region algorithm with interior back - tracking and subspace techniques for nonlinear optimizations subject to linear inequality constraints.
使用仿射变换内点回代技术的信赖域子空间算法解线性不等式约束的非线性优化问题。
The KKT conditions of a nonlinear programming with linear inequality constrains can be transformed into a system of equations by NCP function. Then it is smoothed by Entropy smoothing function.
带不等式约束的非线性规划，其KKT条件可以通过NCP函数转化为一个非光滑的方程组，然后用熵光滑化函数光滑化，得到一个带参数的方程组。
The KKT conditions of a nonlinear programming with linear inequality constrains can be transformed into a system of equations by NCP function. Then it is smoothed by Entropy smoothing function.
带不等式约束的非线性规划，其KKT条件可以通过NCP函数转化为一个非光滑的方程组，然后用熵光滑化函数光滑化，得到一个带参数的方程组。
应用推荐