有一个极值问题，也有关于拉格朗日乘数法的，链式法则也会有的,约束条件下偏导数当然不会漏掉。
Expect one about a min/max problem, something about Lagrange multipliers, something about the chain rule and something about constrained partial derivatives.
本文中，利用目标函数或约束条件的几何性质，提供了某些多元函数极值或最值问题的几何解法。
In the paper, it provides the geometrical solution to extreme value of many variables function by geometric properties of objective function or constraint condition.
运用此定理，在线性空间中建立了带广义不等式约束的向量极值问题的最优性条件。
By the alternative theorem, the optimality conditions of vector extremum problems with generalized inequality constraint are established in linear space.
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