I am having serious issues with comprehension of this method. In particular, I don't understand the conditions. Thus far, I think it's something like;
Given an objective $f: A \to \mathbb{R}^1$ and a constraint $g: A \to \mathbb{R}^1$, wherein $C = \{ x \in A | \,\, g = 0 \}$ is the constraint region, such that $f, g$ have continuous partial derivatives in $C$ and if $\nabla g \not= 0$ on $C$, then we have $\nabla f = \lambda \nabla g$ at any local maximum or minimum constrained to $C$.
Now, what I don't understand is how to deal with the problem of global maxima constrained to $C$, or why $C$ has to be compact (and does $A$ need to be compact)?
And, $C$ has to be an open set, correct? As Lagrange multipliers does not give extrema on the boundary $\partial C $?
(An example illustrating this would be helpful).