| 1. | The affine scaling algorithm for convex programming with linear constraints
线性约束凸规划问题的仿尺度算法 |
| 2. | The improved method is more efficient to derive linear constraints
改进后的方法建立线性约束系统的效率更高。 |
| 3. | Research on the genetic algorithms for linear constraint optimization problems
线性约束优化问题的遗传优化方法研究 |
| 4. | In operations research , a procedure for locating the maximum or minimum of a linear function of variables that are subject to linear constraints
在运筹学中,找出受线性约束的变量的线性函数的最大值或最小值的过程。 |
| 5. | There are many existing algorithms that solve the maximin or minimax programming without constraint or with linear constraints . some of the algorithms need the 2nd order differential information of objective functions
人们已提出了一些求解maximin (或minimax )规划的算法，这些算法要求规划问题无约束或具有线性约束，以及要求有关函数的二次微分信息 |
| 6. | The module conversion for a kind of max - min problems is given , namely , the max - min problem with equality and inequality constraint is converted into convex problem with linear constraint , which provides theoretical basis for designing effective algorithms
最后，给出一类极大极小问题的模型转化，把带等式、不等式约束的极大极小问题转化为带线性约束的凸规划问题，这为设计更为有效的算法提供了理论依据。 |
| 7. | Normally , we try to get the dual form of mathematical programming to change primary programming , which is difficult to be solved into its dual programming , which is easily to be solved . after we had got the dual form of two programming , we found their form were very simply because they had only nonnegative and linear constraints
通常，我们求出规划问题的对偶形式是希望将不易求解的原问题转化为易于求解的对偶问题，在分别得到这两类问题的对偶形式后，发现其形式简单，只带有非负约束和线性约束。 |
