I have a problem, for predefined $x_0,z\in\mathbb{R}$, which looks like $$\min_{\alpha,x} \sum_{i=1}^n \alpha_i f_i(x_i,z) $$ subject to \begin{align} \sum_{i=1}^n \alpha_i &= 1 \\ \sum_{i=1}^n \alpha_i x_i &= x_0 \\ 0 \le \alpha_i, x_i &\le 1, \quad\forall i=1,\dotsc,n. \end{align} We don't know much useful about the $f$ functions, other than that they are continuous and bounded below. They are certainly nonlinear and nonconvex. They are defined by a large set of input data which are fixed for the problem. This problem is solved for local minima, and we have heuristics for finding a supposed global minimum (by sampling the space pseudo-randomly).
There is always one $f_k$ which as $z$ increases takes a lower value than all other $f_i$. So for sufficiently large $z$ the solution is always $a_k=1$, $x_k=x_0$, and all other $\alpha_i=0$, with other $x_i$ values irrelevant. We always know what $k$ is for a given set of input data defining the $f_i$.
What I want to do now is find that critical minimum value of $z$ above which $\alpha_k=1$. The problem would look like $$\min_z z$$ subect to \begin{align} f_k(x_0,z) &\le \min_{\alpha,x} \sum_{i=1}^n \alpha_i f_i(x_i,z) \\ \sum_{i=1}^n \alpha_i &= 1 \\ \sum_{i=1}^n \alpha_i x_i &= x_0 \\ 0 \le \alpha_i, x_i &\le 1, \quad\forall i=1,\dotsc,n. \end{align}
My question is
What is this kind of problem called?
I am trying to do a literature search and not having much success. "Optimization constrained optimization problem", or "problem with optimization constraint," might be my intuitive guess at a name.
In addition to a searchable name for the type of problem this is, if you have pointers to literature on methods of solution, or descriptions of those methods, that's even better.
Have a look at bilevel programming. In general such a problem cannot be readily solved, despite it being quite wide spread. Your best options are reformulating it as one NLP problem, or making your own branch and bound assuming you have some integers. At least those are the two options I'm aware of, but I would love to hear more suggestions, as I have similar problems.