Let $S\subset \mathbb{R}^n$ and let $f(x)$ be a continuous function over $\mathbb{R}^n$. Furthermore, define $s_{\text{max}}:= \sup_{x\in S} \{f(x)\}$ and let $f(x)$ attain its minimum for at least one element in $S$.
Under what conditions on $f(x)$ and $S$ does it hold that $f(x_1)\leq s_{\text{max}}$ $\Rightarrow$ $x_1\in S$?
In particular, does this hold if $f(x)$ is a convex function and $S$ is a convex set? If $f(x)$ is convex and $S$ is an arbitrary set?
Unfortunately I am far from my comfort zone here, so any help is much appreciated!
Let $\Sigma_S = \{x | f(x) \leq \sup_{t \in S} f(t) \}$. If $x \in S$, then we have $f(x) \leq \sup_{t \in S} f(t)$, hence $x \in \Sigma_S$, i.e, $S \subset \Sigma_S$. This is true for all $S,f$.
The desired property above is equivalent to $\Sigma_S \subset S$, hence this is true iff $S = \Sigma_S$.
That is, the property you desire is true iff $S$ has the form $\{x | f(x) \leq L \}$ for some $L$ (which may be $\infty$).
For a counterexample, choose the convex function $f(x) = x^2$ on the convex set $[0,1]$. It is easy to see that $s_\max =1$, but $f(-1) \leq 1$ also.