采用椭球剖分策略剖分可行域为小的椭球，用投影次梯度算法解松弛二次规划问题的拉格朗日对偶问题，从而获得原问题的一个下界。
A projection subgradient algorithm for the Lagrangian dual problem of the relaxed quadratic problem is employed to general lower bounds of the optimal value for the original problem.
本文给出了半无限二次规划和它的对偶规划之间没有间隙的条件。
The conditions under which there is no duality gap between the semi-infinite quadratic programming and its dual programming are given.
在第三章，我们提出了一种解决具有边界约束的正定二次规划问题的对偶方法。
In chapter 3, we presented a dual method for solving positive definite quadratic programming with box constraints.
将优化模型转化为对偶规划，减少了设计变量的数目，并利用序列二次规划求解，缩小了模型的求解规模。
The optimization model was translated into a dual programming and solved by the sequence second-order programming. The number of the variable was reduced and the model's scale was minified.
提出了基于线性变分不等式的原对偶神经网络，并将其作为所对应的二次型规划方案的实时求解器。
A primal-dual neural network(PDNN)based on linear variational inequalities(LVIs)is introduced as the real-time solver for the resultant quadratic programming scheme.
提出了基于线性变分不等式的原对偶神经网络，并将其作为所对应的二次型规划方案的实时求解器。
A primal-dual neural network(PDNN)based on linear variational inequalities(LVIs)is introduced as the real-time solver for the resultant quadratic programming scheme.
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