# Tagged Questions

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### Eliminating variables in convex program

This is a basic convex optimisation question. I have the following problem: $$\max_{\substack{t\le e\\ At\le b}} e^\top t$$ How do I find the optimum $t^*$? I write the KKT conditions, get ...
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### Let $P$ be a polyhedron. Prove, $P$ has at least one extreme point $\iff$ $P$ does not contain a line, by using a lemma.

Let $P$ be a polyhedron. Prove, $P$ has at least one extreme point $\iff$ $P$ does not contain a line, by using a lemma. I've a Lemma saying: Suppose $P=P(V,E)$ where $V,E \in \mathbb R^n$ are ...
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### Mappings preserving convex polyhedra

It is known that linear mappings between euclidean spaces map convex polyhedra to convex polyhedra. Can you give a characterization of the class of mappings that preserve convex polyhedra?
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### Is this a linear programming problem

If $x \in R^n$, then $\min \|x\|_{\infty}$ sub to $Ax = b$, $x \geq 0$ where $\|x\|_{\infty}$ is the infinity norm which is $\max\{\|x_1\|,\|x_2\|,\ldots,\|x_n\|\}$. If not then how can ...
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### A particular ILP where the existence of a relaxed solution implies the existence of an integer solution

This question emerged from a discussion on my previous question Determining quickly whether this Integer Linear Program has any solution at all, which I would like to elaborate separately. I am ...
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### Find a convex combination of scalars given a point within them.

I've been banging my head on this one all day! I'm going to do my best to explain the problem, but bear with me. Given a set of numbers $S = \{X_1, X_2, \dots, X_n\}$ and a scalar $T$, where it is ...
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### Convex function from Hessian

Am I correct to say that the following function is convex? \begin{align} & f(x,y)=-\sqrt{xy} \\ & x>0,y>0 \\ \end{align} After computing the Hessian:  Hf =\left[ \begin ...
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### Farkas Lemma proof

I am trying to prove the Farkas Lemma using the Fourier-Motzkin elimination algorithm. From Wikipedia: Let A be an $m \times n$ matrix and $b$ an $m$-dimensional vector. Then, exactly one of the ...
If you define the convex hull of a set $X$ as the set of all convex combinations of elements of $X$, it becomes difficult to decide if a given element $w$ belongs or not to $conv(X)$ (You have to ...
The problem is to prove Helly's theorem for the case, when the convex bodies are polytopes, by using linear programming duality. Helly's theorem Let $B_{1},...,B_{m}$ be a collection of convex ...