To get so - called c - best - approximate solutin on a certain constrained set c , we employ the constrained regularization method to solve fredholm integral equation of the first kind with nonnegative constraints 为得到所谓的带约束的反问题在特定约束集c上的最优解，我们采用约束正则化方法解决非负约束情况下的第一类fredholm积分方程。
2.
This paper applies generalized multipler method to translate convex quadratic programs with equal constraints and non - negative constraints into simple convex quadratic programs with non - negative constraints . the new algorithm is gotten by solving the simple quadratic program . it avoids the computation of inverse matrix and exploits sparsity structure in the matrix of the quadratic form . the results of numerical experiments show the effectiveness of the algorithm on large scale problems 根据广义乘子法的思想，将具有等式约束和非负约束的凸二次规划问题转化为只有非负约束的简单凸二次规划，通过解简单凸二次规划来得到解等式约束和非负约束的凸二次规划新算法，新算法不用求逆矩阵，这样可充分保持矩阵的稀疏性，用来解大规模稀疏问题.数值结果表明：在微机486 / 33上就能解较大规模的凸二次规划
3.
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。
