convex programming

Convex analysis, Lagrangian relaxation, non differentiable optimization, and applications in integer programming.

凸分析 、 拉格朗日松弛法 、 不可微分函数最适化以及在整数规划上的应用.

The discriminance methods and expression of generalized alternative optimum solutions of linear programming is given by proving that the equivalent of optimum extreme point and extreme point of optimum solution sets of linear programming and applying the theorem of convex polyhedron.

通过证明线性规划最优解集的极点与线性规划最优极点的等价性，利用凸多面体的表达定理，给出了广泛意义下线性规划无穷多最优解的判别方法及表达式。

An on-line training algorithm is presented to avoid repetitious solving the convex programming problem.

并给出一种？着调整时的在线训练算法，避免重复求解凸规划问题。

In this peper some sufficient optimality conditions and duality theorems are obtained for a semi-infinite programming problem in the symmetrically differentiable generalized convex functions and the set of active constraints index is infinite countable set case.

在对称可微广义凸函数、起作用约束指标集为无穷可数集的情形下，得到了半无限规划的几个最优性充分条件和对偶性定理。

Genetic algorithm written in C #. It can be used to solve TSP, Time non-convex programming problems.

运用c # 语言实现模拟退火算法, 同时利用该算法解决旅行商(TSP)问题,获得遍历所有城市序号的最优路径.