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25 votes
2 answers
2k views

An Interesting Optimization Problem

You are given n non-negative integers $a_1, a_2 ,, a_n$. In a single operation, you take any two integers out of these integers and replace them with a new integer having value equal to difference ...
Praveen Dhinwa's user avatar
13 votes
3 answers
835 views

Famous theorems that are special cases of linear programming (or convex) duality

The max flow-min cut theorem is one of the most famous theorems of discrete optimization, although it is very straightforward to prove using duality theory from linear programming. Are there any ...
7 votes
0 answers
1k views

Closed-form solution of a linear programming question

Among all the probability matrices \begin{equation*} P = \left(\begin{array}{cccc} p_{00} & p_{01} & \ldots & p_{0,J-1} \\ p_{10} & p_{11} & \ldots & p_{1,J-1} \\ \vdots & \...
Jerry Jiannan Lu's user avatar
6 votes
1 answer
779 views

If $\ell_0$ regularization can be done via the proximal operator, why are people still using LASSO?

I have just learned that a general framework in constrained optimization is called "proximal gradient optimization". It is interesting that the $\ell_0$ "norm" is also associated with a proximal ...
ArtificiallyIntelligent's user avatar
6 votes
0 answers
97 views

Finding the optimal mixture of two convex functions

I am trying to find an efficient way to solve the problem $$\min_{p,x_1,x_2} p\cdot f(x_1)+ (1-p) \cdot f(x_2)~~~~~ s.t.\\p\cdot g_1(x_1) + (1-p)\cdot g_2(x_2)\leq 1 \\ 0\leq p \leq 1$$ where $x_1,x_2\...
Robert Lowell's user avatar
5 votes
2 answers
2k views

Multiplicative gradient descent?

The normal gradient descent is additive: $w_{t+1}=w_t-\lambda_t\nabla f(w_t)$, but is there a multiplicative gradient descent that looks something like $w_{t+1}=w_t[-\lambda_t\nabla f(w_t)]$? I know ...
thinkbear's user avatar
  • 211
5 votes
1 answer
2k views

Algorithm to minimally connect line segments in Euclidean plane

Suppose you have finitely many line segments in the Euclidean plane. How do you "connect them to form one chain of line segments of minimal length?" More formally and generally, what I'm looking for ...
Xoph's user avatar
  • 153
5 votes
1 answer
176 views

Efficient counting of integer solutions to linear system

In my research, I have a particular 18x18 matrix $\mathbf{A}$ which defines the linear system $\mathbf{A}\cdot \mathbf{x} \leq \mathbf{-1}$ over the nonnegative integers. And I'm interested in ...
user326210's user avatar
5 votes
1 answer
146 views

How does one go from convexity to submodularity?

If I have a function which is convex in the hypercube, $[-1,1]^n$ then when would it imply that its restriction to $\{-1,1\}^n$ is submodular? It would be helpful is someone can share some specific ...
user6818's user avatar
  • 1,893
5 votes
1 answer
3k views

Maximizing supermodular functions

I have a real supermodular objective function which I want to maximize with constraint. The constraint is on the size, like |A|=k . I am wondering if anyone can give me more information about a ...
Majid Yazdani's user avatar
5 votes
0 answers
167 views

A specific case of the $p$-center problem

Given a fixed positive integer $m$, let $\cal{S}$ be the subset from $\mathbb{R}^m$ defined as $\cal{S} = \{u \in \mathbb{R}^m \mid \forall i \in \{1, \dots, m\}, u(i) > 0$ and $\sum_{i=1}^m{u(i) = ...
user109711's user avatar
4 votes
3 answers
1k views

Minimax theorem on a non convex domain

A minimax theorem is a theorem which states that under certain conditions on $\mathcal{X}$, $\mathcal{Y}$ and $f$: $$ \inf_{x \in \mathcal{X}}{\sup_{y \in \mathcal{Y}}{f(x,y)}} = \sup_{y \in \mathcal{...
Adrien's user avatar
  • 591
4 votes
1 answer
3k views

Find the minimum distance between two convex hulls

We work over $\mathbb{R}^N$. Let $\mathbf{P}_1$ denote the hyperplane constructed using $N$ points, each of which is on a different axis (there are $N$ axes). We denote by $\mathbf{P}_2$ the convex ...
tam's user avatar
  • 233
4 votes
1 answer
3k views

optimization of inverse matrix with constraint on matrix elements

everyone! I have this optimization problem with constraint. $D$ and $T$ are symmetric matrices, where T is known and D is the unknown parameter. $x$ and $v$ are two known p-dimensional vectors. The ...
Bing's user avatar
  • 49
4 votes
1 answer
288 views

Equivalent method for maximum likelihood estimation of covariance parameters

My goal is to estimate the parameters of a covariance matrix $\Omega$, by maximizing the following log-likelihood function: $$\log L(\vec\tau, \rho, \sigma \mid W, X) = -m\ln(\left | \Omega \right |) ...
Ruben van Bergen's user avatar
4 votes
0 answers
539 views

Using Linear Programming as an iterative procedure

Suppose, we have a linear program and an optimal solution to it. Suppose now, we get a new constraint. We want to obtain an optimal solution to the given linear program extended by that new constraint....
D. Rusin's user avatar
  • 391
3 votes
1 answer
266 views

Strong polynomial algorithm for linear programming

What is the current state of finding a strong polynomial algorithm for linear programming? Is there any reference?
Hao Yu's user avatar
  • 781
3 votes
3 answers
349 views

Sensitivity analysis in conic optimization

I have a conic optimization of the form: $$\min_x \langle c, x \rangle,\ \text{s.t.}\ Ax = b,\ x \in K.$$ where $x \in \mathbb{R}^{n}$, $A$ is an $m \times n$ matrix, $b \in \mathbb{R}^m$, $K$ is a ...
Barrett's user avatar
  • 143
3 votes
1 answer
275 views

Uniqueness of l1 minimization

Let $A \in \mathbb{R}^{m \times n}$. Is it true that $$\min \limits_{Q \in \mathbb{R}^{n \times m}}|I - QA|_{\infty} < \frac{1}{2}$$ is criteria for the uniqueness of the 1-sparse solution to $\...
love_backups's user avatar
3 votes
2 answers
792 views

Has anyone developed a technique to generate a polytope given (possibly redundant) inequality constraints? [closed]

I've found a few papers that deal with removing redundant inequality constraints for linear programs, but I'm just trying to find the vertices for a feasible region, given a set of inequality ...
Nick Sweet's user avatar
3 votes
1 answer
4k views

Schur complement and negative definite matrices

Hello, My question regards to the Schur complement lemma. Consider the matrix $M=\left( \begin{array}{cc} A & B\\\ B^T & C \end{array}\right) $. According to the lemma $M\geq0$ iff $C>0$ ...
AD1984's user avatar
  • 155
3 votes
0 answers
282 views

Continuum of Lagrange multipliers, duality gap, and minimax theorem

Suppose I have a linear optimization problem involving random variables on some (infinite) probability space $\Omega$. For example, need to maximize expectation $E[Q]$ of random variable $Q$ subject ...
Bogdan's user avatar
  • 781
3 votes
0 answers
122 views

Convex optimization upper bound for a non-linear optimization

Is there any good convex optimization problem based upper-bound for the following non-linear optimization problem? \begin{align} \max_{x_1,\ldots,x_N}&\quad \sum_{n=1}^{N} \log(1+\frac{x_n}{1+\...
Math_Y's user avatar
  • 287
3 votes
1 answer
368 views

Lot sizing problem: how to add these cuts efficiently

Consider the set of constraints of the uncapacitated lot sizing problem: $$ \{(x,s,y)\in \mathbb{R}^n_+ \times \mathbb{R}^n_+ \times \mathbb{B}^n \;|\;s_{t-1}+x_t = d_t+s_t,\; x_t \le My_t,\; t=1,\...
Kuifje's user avatar
  • 225
3 votes
0 answers
71 views

Dependence of optimization problem on the linear constraints

Let $I=\{x_1,\cdots, x_n\}\subset \mathbb R$ be fixed. Given two probability distributions $\alpha=(\alpha_i)_{1\le i\le n}$ and $\beta=(\beta_i)_{1\le i\le n}$ on $I$, and a matrix $c=(c_{i,j})_{1\le ...
CodeGolf's user avatar
  • 1,835
2 votes
3 answers
2k views

Better tactics for removing redundant constraints than Linear Programming?

After reading: Detection of Redundant Constraints It appears that linear-programming is the most commonly known way to remove ALL redundant constraints from a system of inequalities of the form $$ ...
Sidharth Ghoshal's user avatar
2 votes
4 answers
212 views

Efficient algorithm for graph problem

Let $D=(V,E)$ be a directed graph, $S,T\subset V$ and $f:V\rightarrow \{1,\ldots, k\}$ a positive, bounded weight-function and $l\in \mathbb{N}$, find a path $v_1,\ldots, v_l\in V$ with $v_1\in S$ and ...
Martin Clever's user avatar
2 votes
3 answers
1k views

Quadratic Programming With Piecewise Linear Term

The problem I have can be defined as: $$ \min \frac{1}{2}\mathbf{x}^T\mathbf{Q}\mathbf{x} + \mathbf{c}^T\mathbf{x} $$ s.t. linear equality constraints: $$ \mathbf{Ax=b} $$ and linear inequality ...
TMS's user avatar
  • 131
2 votes
1 answer
243 views

Does quantifier elimination help here?

Suppose we have a quantified linear program $$\exists z_1,\dots,z_{poly(n)}\in\mathbb R$$ $$\exists u_1,\dots,u_n\in\mathcal P\cap\mathbb R^m$$ $$\forall v_1,\dots,v_n\in\mathcal P\cap\mathbb R^m$$ $$...
VS.'s user avatar
  • 1,826
2 votes
1 answer
186 views

How can I find the maximum value of this function?

For given values of $A \in \mathbb{R}^{m \times n}, b \in \mathbb{R}^m$, how can I find the value of: $$ \max_{x \in [0,1]^n} \|Ax+b \|_1 $$ Or is this problem NP-hard?
OleS's user avatar
  • 23
2 votes
1 answer
276 views

An optimization problem in complex space

Consider the following optimization problem $$ \min \| \textbf{Ax-B}\| $$ $$ s.t.|x_i|=1,i=1,...,n $$ where $\textbf{x}\in \mathbb{C}^{n}$ is the optimization varaible, $x_i$ is the $i$-th ...
Denny's user avatar
  • 21
2 votes
1 answer
130 views

Fastest 'Oracle' Algorithm for satisfying a single linear constraint on a convex set?

In this paper by Arora, Hazan, and Kale (http://www.cs.princeton.edu/~arora/pubs/MWsurvey.pdf) a method is given for using the Multiplicative Weights Update algorithm to quickly solve Linear Programs ...
Sam Stern's user avatar
  • 121
2 votes
1 answer
91 views

Linear program with one quadratic condition convex in domain of interest polynomial time solvable?

$c\leq xy$ is not a convex condition. However we know $c\leq xy$ is convex in domain $x,y>0$ in $\mathbb R^2$ for any fixed $c\in\mathbb R$. Is $c\leq x_1y_1+\dots+x_ny_n$ with $0\leq x_1,\dots,...
Turbo's user avatar
  • 13.9k
2 votes
1 answer
509 views

Under what condition does Courant–Fischer–Weyl min-max principle hold in general?

From Wikipedia: Let $A$ be an $n \times n$ Hermitian matrix. As with many other variational results on eigenvalues, one considers the Rayleigh–Ritz quotient $R_A : \mathbf C^n \setminus \{0\} \to \...
Fraïssé's user avatar
  • 155
2 votes
2 answers
799 views

Survey on Compared Running Time: Ellipsoid Method vs. Simplex Method

If you look through papers on the Ellipsoid Method, there is a large agreement, that the Ellipsoid Method, although theoretically polynomial, is in practice way slower than the Simplex Method. ...
Skrodde's user avatar
  • 329
2 votes
0 answers
119 views

Seeking insights on bounded set positive solutions for a set of linear systems in $\mathbb{R}^n$

Before delving into my query, I'd like to provide some context. Consider a continuous function $f:\mathbb{R}^{k}\rightarrow\mathbb{R}^{m}$ and a compact set $\mathcal{B}\subset \mathbb{R}^{k}$ (...
Diego Fonseca's user avatar
2 votes
0 answers
46 views

Notion of distance between linear programs

Consider the linear programming problem \begin{align} \max_{x}&~c^Tx \\~s.t.~~a^Tx &\leq B~,~0\leq x_i \le1 \end{align} where $c$ and $a$ are $n \times 1$ given non-negative vectors. $B$ is a ...
dineshdileep's user avatar
  • 1,421
2 votes
0 answers
66 views

Proving the existence of a dual for an infinite linear program

I am concerned with proving the existence of the dual of an infinite linear program. In addition to the writings of Rockafellar, Luenberger, and Boyd & Vandenberghe on: subdifferentials, Legendre-...
teddy's user avatar
  • 121
2 votes
0 answers
283 views

Derivative with multiple summation operators

I have a defined utility function as Eq.(1), and I am seeking the minimized utility subjects to some constraints. The notation used is as following: \linebreak $V$ is the set of nodes, $v_i\in V$; $O$...
Dehao 's user avatar
  • 21
2 votes
0 answers
105 views

Optimization over a convex cone generated by a set is equal to optimization over the set

Within my research I found an important doubt and that prevents me from advancing, the context of my doubt is as follows: We considerer the following optimization problem $$ \left\{\begin{array}{cl} \...
matematicaActiva's user avatar
2 votes
0 answers
299 views

Practical application of envelope theorem for linear programs

Assume that we have solved a (standard) linear program $$ \text{minimize}_{x\in {\mathbb R^n}}\,\, c_0^Tx, \,\,\,\,\, \text{s.t. } A_0x \leq b_0, $$ and would like to know how sensitive is the optimal ...
Bogdan Grechuk's user avatar
2 votes
0 answers
64 views

Finding orthogonal basis with constraint

Is there any fast algorithm that output an orthogonal basis $e_i,i\leq n$ of $R^n$ with $e_i\in V_i$? Where $V_i,i\leq n$ are given linear subspaces of $R^n$. And is there any condition on $V_i,i\leq ...
Jiayi Liu's user avatar
  • 909
2 votes
0 answers
210 views

Finding optimal linear transformation for intersection of convex polytopes

I previously posted this on MathSE and am now trying here. I have the following situation, as shown in the following diagram: $W=\{w_i\}_{i=1..|W|}$ is a set of vertices (show in diagram in blue) ...
Artemy's user avatar
  • 695
2 votes
0 answers
149 views

How to solve the following generalized quadratic programming problem [closed]

I want to solve a generalized form of a quadratic programming problem $$\min_x \left(\sqrt{x^TPx}+\sqrt{x^TQx}\right)^2+c^Tx$$, $$\textrm{ s.t. } Ax\le b.$$ Here, $P$ and $Q$ are both positive ...
ListenTee's user avatar
1 vote
2 answers
150 views

investigating positivity/negativity of a function [closed]

I'm investigating if and how the positivity or negativity of a multivariable function can be proved. Consider $y_{1},y_{2},y_{3}\in\mathbb{R}$ and the following function $$f\left(y_{1},y_{2},y_{3}\...
alperden15's user avatar
1 vote
2 answers
83 views

Algorithm for a linear optimization problem

For the vectors $X=(x_1,\cdots, x_n),~ Y=(y_1,\cdots, y_n)$ and $\alpha=(\alpha_1,\cdots,\alpha_n),~ \beta=(\beta_1,\cdots, \beta_n)\in\mathbb R^n_+$ s.t. $\sum_{k=1}^n\alpha_k~~=~~\sum_{k=1}^n\beta_k~...
Higgs88's user avatar
  • 131
1 vote
1 answer
106 views

Iterated optimal transport

Suppose we are interested in two consecutive transport plans (in the Kantorovich formulation). That is, we are given finite sets $X$, $Y$ and $Z$, endowed with probability measures $\mu_X$, $\mu_Y$ ...
tex.support's user avatar
1 vote
2 answers
121 views

How to solve the optimization problem $\max_{\mathbf{w}}\sum_i\text{sign}(\mathbf{w}^T \mathbf{x}_i)$?

I am looking for an algorithm to solve the following optimization problem $$\max_{\mathbf{w}}\sum_i\text{sign}(\mathbf{w}^T \mathbf{x}_i)$$ where $\mathbf{w}$ and each $\mathbf{x}_i\in\mathbb{R}^d$. ...
user3750444's user avatar
1 vote
1 answer
126 views

Quantifier elimination and where is this quantified convex program in the polynomial hierarchy?

I have a quantified convex program of the form that I need to solve $$\exists(x_{1,1},\dots,x_{1,n})\in\mathbb R^n\quad\forall(x_{2,1},\dots,x_{2,n})\in\mathbb R^n$$ $$\vdots$$ $$\exists(x_{2t-1,1},\...
VS.'s user avatar
  • 1,826
1 vote
1 answer
123 views

LASSO problem but with a maximization instead of minimization

I have the following optimization problem (like the LASSO problem but with maximization instead of minimization): $\mathbf{maximize}_{\boldsymbol{\alpha}} \|\mathbf{x} -\mathbf{A}\boldsymbol{\alpha}\|...
Christina's user avatar
  • 111