$X$ is a nonempty convex subset of $\mathbb{R}^n$ whose element is $x=\left(x_1,...,x_n\right)$.

The theorem is as follows.

If for each $x\in X$, there is an $i \in \left\{1,...,n\right\}$ such that $x_i>0$, then there exists $\left(\lambda_1,...,\lambda_n\right)$ where $\lambda_i \geqslant 0$ for all $i$ and $\sum_{i=1}^n \lambda_i=1$, such that $\lambda \cdot x \geqslant 0$ for all $x\in X$ and $\lambda \cdot x>0$, for some $x \in X$.

I was wondering how to prove it. "$\geqslant 0$ for all $x$" should be easy. But I got stuck in "$>0$ for some $x$". I failed to use the proper separation theorem (Theorem 11.3 in Rockafellar (1970)).

Thank you very much!

This was cross-posted at https://math.stackexchange.com/questions/4504475/how-to-prove-this-corollary-of-hyperplane-separation-theorem?noredirect=1#comment9461236_4504475

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3 Answers 3


Let $Y$ be the span of $X$, $C=Y\cap (-\infty,0]^n$. Since $X$ and $C$ are disjoint convex sets in $Y$, there exists a non-zero functional $\eta\in Y^*$ which separates (not strictly) $X$ and $C$: $\eta$ is non-positive on $C$ and non-negative on $X$. Since $X$ is of full dimension in $Y$, we have $\eta(x)>0$ for some $x\in X$.

Now note that the coordinate functionals $x\to x_i$, $i=1,\ldots,n$, and the functional $\eta$ on $Y$ satisfy the property "if $x_i$'s are non-negative, then $\eta$ is non-negative". It yields by duality that $\eta$ is a non-negative linear combination of $x_i$'s (as a functional on $Y$, in particular as a function on $X$.)

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    $\begingroup$ @WlodAA $Y$ is used to find a point $x\in X$ in which $\eta(x)\ne 0$ $\endgroup$ Aug 10 at 6:17
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    $\begingroup$ oh, you are correct. Let's say differently: the coordinate functionals $x\to x_i$ and the functional $\eta$ on $Y$ satisfy the property "if $x_i$'s are non-negative, then $\eta$ is non-negative". It yields by duality that $\eta$ belongs to a cone generated by $x_i$'s. $\endgroup$ Aug 10 at 14:42
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    $\begingroup$ @copper.hat on $Y$ every functional may be represented as a non-negative linear combination of $x_1$ and $x_2$. $\endgroup$ Aug 12 at 4:55
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    $\begingroup$ any finitely generated cone is closed (it is a finite unit of cones generated by linearly independent subsets: if $g=c_1f_1+\ldots+c_kf_k\,(*)$ with all $c_1,\ldots,c_k$ positive, but $f_i$'s are linearly dependent, then adding this dependence with appropriate coefficient to $(*)$ you get a representation of $g$ with lesser number of f's.) $\endgroup$ Aug 12 at 14:37
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    $\begingroup$ @Ypbor If $\eta$ vanishes on $X$, then it vanishes on $Y$, while it is a non-zero functional. Then there is $x \in X$ such that $\eta(x)\neq 0$ and then $\eta (x)>0$ since $\eta \geq 0$ on $X$. $\endgroup$ Aug 13 at 14:30

$\newcommand{\R}{\mathbb R}\newcommand{\la}{\lambda}$Let $\R_-:=(-\infty,0]$ and $\R_+:=[0,\infty)$. The desired statement is equivalent to the following:

Suppose that \begin{equation*} \forall x\in X\ \exists i\in[n]:=\{1,\dots,n\}\ x_i>0. \tag{1}\label{1} \end{equation*} Then there is some $\nu\in\R_+^n$ such that \begin{equation*} \nu\cdot X:=\{\nu\cdot x\colon x\in X\}\subseteq\R_+\quad\text{and}\quad \nu\cdot X\ne\{0\}. \tag{2}\label{2} \end{equation*}

Proof: Condition \eqref{1} means that $X\cap\R_-^n=\emptyset$. So, by Theorem 11.3 in Rockafellar (1970), there is some $\la^1\in\R^n\setminus\{0\}$ such that $\la^1\cdot X\subseteq\R_+$ and $\la^1\cdot\R_-^n\subseteq\R_-$. Also, $\la^1\cdot\R_-^n\subseteq\R_-$ means that $\la^1\in\R_+^n$. Thus, \begin{equation*} \text{$\la^1\in\R_+^n\setminus\{0\}$ and $\la^1\cdot X\subseteq\R_+$.} \tag{3}\label{3} \end{equation*}

So, either \eqref{2} holds with $\la^1$ in place of $\nu$ or $\la^1\cdot X=\{0\}$.
So, without loss of generality (wlog), $\la^1\cdot X=\{0\}$. That is, we have \begin{equation*} X\subseteq V^1:=\{x\in\R^n\colon\la^1\cdot x=0\}. \end{equation*} The condition $\la^1\in\R_+^n\setminus\{0\}$ in \eqref{3} implies that wlog for some $k^1\in[n]$ and all $i\in[n]$ \begin{equation*} \la^1_i>0\text{ if }i\le k^1\quad \text{and}\quad \la^1_i=0\text{ if }i>k^1. \tag{4}\label{4} \end{equation*}

Now condition \eqref{1} implies $X\cap V^1_-=\emptyset$, where $V^1_-:=V^1\cap\R_-^n$. Applying now Theorem 11.3 in Rockafellar (1970) to the Euclidean space $V^1$, we see that there is some $\mu^1\in V^1\setminus\{0\}$ such that \begin{equation*} \mu^1\cdot X\subseteq\R_+ \end{equation*} and $\mu^1\cdot(V^1\cap\R_-^n)\subseteq\R_-$. The latter condition means that for all $x\in\R^n$ we have \begin{equation*} (\la^1\cdot x=0\ \&\ x\in\R_-^n)\implies\mu^1\cdot x\le0 \end{equation*} or, equivalently, \begin{equation*} (\la^1\cdot x=0\ \&\ x\in\R_+^n)\implies\mu^1\cdot x\ge0. \tag{5}\label{5} \end{equation*} Substituting the $i$th standard basis vector $e_i$ for $x$ in \eqref{5}, and recalling \eqref{4}, we get $\mu^1_i=\mu^1\cdot e_i\ge0$ for $i>k$.

So, wlog there is some real $t^1>0$ such that for \begin{equation*} \la^2:=\la^1+t^1\mu^1 \tag{6}\label{6} \end{equation*} and some integer $k^2\in[k^1,n]$ we have \begin{equation*} \la^2_i>0\text{ if }i\le k^2\quad \text{and}\quad \la^2_i=0\text{ if }i>k^2. \tag{4a}\label{4a} \end{equation*} Also, by \eqref{6}, $\la^2\cdot X\subseteq\la^1\cdot X+t^1\mu^1\cdot X\subseteq\R_+$. So, either \eqref{2} holds with $\la^2$ in place of $\nu$ or $\la^2\cdot X=\{0\}$ and hence $\mu^1\cdot X=\{0\}$.
So, wlog, $\la^2\cdot X=\{0\}=\mu^1\cdot X$. So, \begin{equation*} X\subseteq V^2:=\{x\in V^1\colon\la^2\cdot x=0\} =\{x\in V^1\colon\mu^1\cdot x=0\}\subsetneq V^1; \end{equation*} the latter strict inclusion follows because $\mu^1\in V^1\setminus\{0\}$.

Continuing thus, in $n$ similar steps wlog we will get $X\subseteq V^n:=\{0\}$, which contradicts \eqref{1}. $\quad\Box$.

  • $\begingroup$ Thanks for answering. I have some questions. (1) How can you guarantee that $\mu^1 \in V^1$? (2) Why is $\left\{x \in \mathbb{R}^n: \lambda^2 \cdot x=0\right\}=\left\{x \in V^1: \mu^1 \cdot x=0\right\}$? Why doesn't $\lambda^1 \cdot x>0$ and $\mu^1 \cdot x<0$ work? (3) Why does $V^n$ eventually shrink to ${0}$? $\endgroup$
    – Ypbor
    Aug 11 at 9:04
  • $\begingroup$ @Ypbor : (1) Theorem 11.3 in the Rockafellar book is stated for $R^n$, but is clearly applicable to any finite-dimensional Euclidean space. I applied this theorem to the subspace $V_1$ of the Euclidean space $\mathbb R^n$, since $X\subseteq V_1$ and $V^1_-\subseteq V_1$. So, we automatically have $\mu^1\in V^1\setminus\{0\}$. (2) The definition of $V^2$ was incorrect. It is corrected now. (3) The inclusion $V^2\subsetneq V^1$ is strict. Continuing such steps, wlog we will get $V^n\subsetneq V^{n-1}\cdots\subsetneq V^1$. Since the dimension of $V_1$ is $n-1$, the dimension of $V_n$ is $0$. $\endgroup$ Aug 11 at 17:30
  • $\begingroup$ @losif Pinelis, the hyperplane is in $V^1$, but $\mu^1$, which is the normal vector, is not in $V^1$. $\endgroup$
    – Ypbor
    Aug 12 at 7:38
  • $\begingroup$ @Ypbor : To understand this point, forget that $V^1$ is a subspace of $\mathbb R^n$ -- look at $V^1$ as a Euclidean space on its own. By Theorem 11.3 in the Rockafellar book applied to $V^1$ (instead of $R^n$), there is (say) a nonzero linear functional $l$ on $V^1$ such that $l(X)\subseteq\mathbb R_+$ and $l(V_-^1)\subseteq\mathbb R_-$. The linear functional $l$ on $V^1$ is given by the formula $l(x)=\mu_1\cdot x$ for some nonzero $\mu^1\in V^1$ and all $x\in V^1$. So, $\mu^1\cdot X\subseteq\mathbb R_+$ and $\mu^1\cdot V_-^1\subseteq\mathbb R_-$. And, of course, $\mu^1\in V^1$. $\endgroup$ Aug 12 at 13:38
  • $\begingroup$ In my graph, $X=\left\{(x_1, x_2) | x_1+x_2=0, x_1 \in [\frac{1}{2},1]\right\}$, $V^1=\left\{(x_1, x_2)| x_1+x_2=0\right\}$, and $V_{-}^1$ is just the origin. Note that the dimension of $V^1$ is 1, so a hyperplane should be of dimension 0. For example, point $A$ is a hyperplane (with respect to $V^1$) that separates $X$ and $V_{-}^1$. Of course, $A \in V^1$, but what is the $\mu^1$ corresponding to $A$? (Note $\mu^1 \in \mathbb{R}^2$) $\endgroup$
    – Ypbor
    Aug 13 at 2:23

I thought that I had an answer for both part, but for the moment, I succeed only on the first part, which is an application of the first separation theorem given in https://en.wikipedia.org/wiki/Hyperplane_separation_theorem

By assumption, $X$ and $\mathbb{R}_-^n$ are two disjoint non-empty convex subsets of $\mathbb{R}^n$. There exist some non-null vector $c$ such that $X \subset \{x \in \mathbb{R}^n : c \cdot x \ge 0\}$ and $\mathbb{R}_-^n \subset \{x \in \mathbb{R}^n : c \cdot x \le 0\}$.

The last condition applied to opposite of the vectors of the canonical basis of $\mathbb{R}^n$ (containd in $\mathbb{R}_-^n$) forces $c$ to have non-negative coordinates. Of course, one may divide $c$ by the sum of its coordinate (which is strictly positive).


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