All Questions
783 questions
6
votes
0
answers
141
views
Algorithm to check a conjectural value for the rank of a large matrix
Feel free to suggest a different title, I'm not sure how to phrase this. I'm in the following somewhat specific situation:
I'm checking a conjecture which at the end of the day boils down to the ...
1
vote
0
answers
163
views
Can we reduce the maximization of this integral to the maximization of the integrand?
I would like to know whether we are able to reduce the following optimization problem to the pointwise optimization of the integrand (or how we can solve it otherwise): Maximize $$\sum_{i\in I}\sum_{j\...
0
votes
1
answer
99
views
Finding dual of a scheduling LP formulation
Suppose I have an LP formulation as such:
$\min\ \ \sum\limits_{i,j,t}\ w_{ij}x_{ijt} (\frac{t-r_j}{p_{ij}}+0.5)$
$\sum\limits_{i,t}\frac{x_{ijt}}{p_{ij}}=1\,\forall\ j$
$\sum\limits_{j}x_{ijt}\leq ...
0
votes
1
answer
113
views
How do I solve this integer programming problem with non convex constraints?
I am not sure if this is the right place to post this question, please point me to the correct forum if I posted in a wrong place.
I have an optimization problem like this
...
0
votes
0
answers
101
views
How can we analytically solve this max-sum-min problem?
Let $I$ be a finite set, and $A_{ij},B_{ij},x_i,y_j\ge0$. I want to find the choice of $x_i,y_j$ maximizing $$\sum_{i\in I}\sum_{j\in J}A_{ij}\min\left(x_i,B_{ij}y_j\right)\tag1$$ subject to $$\sum_{i\...
0
votes
1
answer
61
views
Variant of the linear programming problem
Good afternoon, my experience in mathematical programming is low. I would like to know if there is any general method to address the following problem:
$$\text{Minimize }\sum_{i=1}^n d_i(x_j)$$
$$s.a....
2
votes
0
answers
148
views
Generalization of Farkas' Lemma to Hermitian Matrices
I recently stumbled upon a well-known version of Farkas' Lemma which, roughly speaking, I would like to generalize from real vectors to hermitian matrices, as it seems promising for something else I ...
0
votes
0
answers
35
views
Converting a vector in a cone statement to inequality constraints
I would like to convert the following condition for $x$
\begin{align}
x = N \lambda, \lambda \geq 0
\end{align}
to a pure linear inequality form, i.e. find an $L$ and eliminate $\lambda$
\begin{...
1
vote
0
answers
25
views
Weird subspace/equality-constrained LP problem/variant of change-making problem
Assume that we have a set, $\mathscr{R}$ containing $m$-dimensional vectors. Solve
$$\sum_{i=1}^n c_i\leq\delta$$
$$\text{subject to } \sum_{i=1}^n r_i c_i=x^\prime \text{ for all }x^\prime$$
where
$0\...
6
votes
1
answer
861
views
Is Binary Integer Linear Programming solvable in polynomial time?
The paper Solving the Binary Linear Programming Model in Polynomial Time claims that Binary Integer Linear Programming is in P. However, it seems that no subsequent literature in the mainstream has ...
3
votes
1
answer
1k
views
Finding the closest special orthogonal matrix in Frobenius norm sense
Given a $3\times3$ matrix $M$, if we would like to get the closest $\mathrm{SO}(3)$ matrix $R$ that minimizes
\begin{equation}
\|R-M\|_F
\end{equation}
then $R$ = $UV^{T}$ where $U$ and $V^{T}$ are ...
1
vote
0
answers
214
views
Effective Jordan normal form
Given $A \in \mathrm{GL}_m(\mathbb{C})$, I can conjugate it by some $B \in \mathrm{GL}_m(\mathbb{C})$ into its Jordan normal form. That is, for some $n\le m$, there exists a $J \in \mathrm{GL}_n(\...
2
votes
1
answer
1k
views
Is it faster to compute eigenvalues or coefficients of characteristic polynomials?
Given $A \in \mathsf{M}_n(\mathbb{C})$ (no special structure) is it (generally) faster to compute its eigenvalues or the coefficients of its characteristic polynomial?
References/insights would be ...
3
votes
1
answer
244
views
What importance does the Hirsch conjecture have to Simplex Complexity?
The Hirsch conjecture asserts that the graph (i.e. $1$-skeleton) of a $d$-dimensional convex polytope with $n$ facets has diameter at most $n - d$.
After being open for decades, Francisco Santos has ...
5
votes
1
answer
315
views
On optimal dual solutions for the minimum weight perfect matching problems in the case of metric weights
Following Lovasz-Plummer (Matching theory, North-Holland 1986, Theorem 9.2.1),
the minimum weight perfect matching problem on a complete graph
$G$ with even number of vertices and weight $w:E(G)\to
\...
3
votes
1
answer
275
views
Uniqueness of l1 minimization
Let $A \in \mathbb{R}^{m \times n}$.
Is it true that $$\min \limits_{Q \in \mathbb{R}^{n \times m}}|I - QA|_{\infty} < \frac{1}{2}$$ is criteria for the uniqueness of the 1-sparse solution to
$\...
1
vote
0
answers
177
views
Prove that these linear programming problems are bounded by $O(k^{1/2})$ [closed]
The expanded partial sums of the Möbius inverse of the Harmonic numbers have two out of three properties in common with this set of linear programming problems:
$$\begin{array}{ll} \text{minimize} &...
5
votes
1
answer
403
views
Best orthogonal approximation of rank 1 matrix
Let $X=\lambda_0u_0v_0^T\in\mathbb{R}^{n\times n}$ be a rank 1 matrix where $\lambda_0\in\mathbb{R}$, $u_0,v_0$ are of unit Euclidean norm. What is the solution of the following problem?
$$\hat{X}=\...
5
votes
1
answer
183
views
Resource Constrained Routing with Refueling
What are good algorithms (resp. models) for calculating optimal or near optimal routes while taking into account fuel consumption, options for refueling and, limited tank capacity?
Especially modeling ...
3
votes
2
answers
331
views
Program to solve Optimization Problem
I have an optimization problem, this problem has linear constraints and nonlinear constraints. I solved the linear part by MATLAB but the nonlinear constraints I could not solve it. I downloaded ...
0
votes
0
answers
232
views
What do square roots as minimums have to do with Harmonic numbers?
In an earlier question where I conjectured (and GH from MO confirmed) that the von Mangoldt function is the limit at s=1 of a certain Dirichlet series:
$$\Lambda(m)=\lim_{s\to 1+}\zeta(s)\sum_{d\mid ...
3
votes
2
answers
676
views
Parametrising a sparse orthogonal matrix
I need to find a way to parametrise a matrix that is both sparse (to some degree) and orthogonal, i.e., I am looking for a parametrisation that describes $A \in \mathbb{R}^{n\times m}$ such that $AA^𝑇...
5
votes
1
answer
424
views
What is the LP gap of vertex cover in planar graphs?
What is the LP gap of vertex cover in planar graphs?
The LP I refer to is min $\sum_{e \in E } c_e x_e \ \ $ subject to $ \ \ x_v + x_u \geq 1 \ \ \ \forall uv \in E $
$ c_e \geq 0 $ are ...
3
votes
0
answers
178
views
Uniqueness of projection under spectral norm
I am considering
$$
\min_{M\in \mathcal{M}} \|X - M\|:=x \neq 0,
$$
where $X$, $M$ are $m\times n$ matrices, $\|\cdot\|$ is spectral norm and $\mathcal{M}$ is a matrix subspace. I wonder to what ...
0
votes
0
answers
83
views
Matrix decomposition in a specific form
Can we prove that for any real valued $d\times d$ matrix $A$, $A$ can be decomposed to finite product of such matrices
$$A=\prod_{i=1}^n (I+R_i)$$
where $I$ is the identity matrix and $\operatorname{...
5
votes
1
answer
171
views
Finite difference for a highly nonlinear equation - The wind within the forest
Based on the Navier-Stokes equations and a few parameterizations, the horizontal steady-state wind $u(z)$ within a forest of height $H$ satisfies:
$$
a\Big(\frac{du}{dz}\Big)^{\!2} + b\frac{du}{dz} \...
4
votes
2
answers
3k
views
Methods of solving linear system of equations, how to select the appropriate method
A linear system of equations Ax=b can be solved using various methods, namely, inverse method, Gauss/Gauss-Jordan elimination, LU factorization, EVD (Eigenvalue Decomposition), and SVD (Singular Value ...
1
vote
0
answers
36
views
Linear programming with a convergent coefficient
The following linear programming problem
$x_n = \arg\min c_n'x \mbox{ subject to } Ax<b$
has a changing coefficient $c_n$. We have that $c_n\rightarrow c_*$. What happens to the solution $x_n$? ...
2
votes
1
answer
243
views
Does quantifier elimination help here?
Suppose we have a quantified linear program
$$\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$$
$$...
3
votes
1
answer
152
views
A question about polytopes related to linear programming
Given linear functions $f_1({\bf x}),\dots,f_n({\bf x})$ on ${\bf R}^m$, let $K = \{(a_1,\dots,a_n) \in {\bf R}^n:$ the $n$ halfspaces $\{{\bf x}: f_i({\bf x}) \leq a_i\} $ have nonempty intersection$\...
1
vote
0
answers
126
views
Mixed integer formulation of union of polytopes?
Given $t$ different unbounded polyhedra $P_1:A^{(1)}x^{(1)}\leq b^{(1)},\dots,P_t:A^{(t)}x^{(t)}\leq b^{(t)}$ we are looking for the representation of $\bigcup_{i=1}^tP_i$ (not their convex hull) with ...
1
vote
0
answers
98
views
L1 Norm regression [closed]
First time poster...apologies for formatting.
I am trying to devise a solution to a familiar linear algebra equation, Ax=b, where all elements in A are non-negative and all the elements in b are ...
0
votes
1
answer
39
views
Gluing simplices through a common point/ realisation of a convex simplicial polytope
Given $m≥d+1$
a positive integer, is it always possible to find m d-dimensional simplices $\Delta_i=\mathrm{Conv}(M,V_{i,1},…,V_{i,d})$ such that
1) they all share the common vertex M
2) the ...
1
vote
0
answers
225
views
Why de-blurring a blurred image is an ill-conditioned problem? [closed]
Why de-blurring a blurred image is an ill-conditioned problem? What's the intuitive explanation? How to show it using the condition number?
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
$$\exists(x_{1,1},\dots,x_{1,n})\in\mathbb R^n\quad\forall(x_{2,1},\dots,x_{2,n})\in\mathbb R^n$$
$$\vdots$$
$$\exists(x_{2t-1,1},\...
7
votes
2
answers
909
views
Formula for volume of a convex polytope
So I've been searching around the internet for some answers to this, but I currently have a set of linear constraints: $Ax = b, Cx \le d$ for matrices $A \in \mathbb{R}^{n \times m}$, $b\in \mathbb{R}^...
4
votes
0
answers
82
views
Is there a fast way to compute the lowest eigenvalue of this symmetric PD matrix in this specific scenario?
Consider
$$C = A^H D A + M$$
where
$A$ is a $m \times m$ unitary matrix.
$D$ is a $m \times m$ diagonal matrix with entries either $0$ or $1$.
The number of $1$'s is $n \ll m$.
$M$ is a $m \times ...
9
votes
1
answer
1k
views
Computation time of Smith normal form in Maple
I am using Maple to compute the Smith normal form (SNF) of a $120 \times 120$ matrix and it seems that I will never get an answer back. I have checked my code for small cases and I believe that it is ...
3
votes
2
answers
3k
views
Sparse approximation of the inverse of a sparse matrix
Is it possible to approximate an inverse of a sparse matrix with a sparse matrix?
The problem comes up in numerical non-linear quasi-Newton optimization: given a sparse Hessian a good starting point ...
1
vote
0
answers
24
views
Simple monotonicity property for coordinate descent and linear objective functions
Let $S \subset \mathbb{R}^n$ satisfy $0\leq x_1\leq\dots\leq x_n$ for all $\mathbf{x}\in S$, among other (possibly nonconvex) constraints, and suppose in addition that $\sum_{i=1}^n x_i \geq 1$ for ...
0
votes
0
answers
89
views
Why there isn't lexicographically smallest solution to a bounded linear program?
I am learning computational geometry when I run into this confusion. "A bounded 2D linear program may not have a lexicographically smallest solution", as the book says. I wonder why? I think we can ...
1
vote
0
answers
37
views
Fast certficate of negativity for objective value of mixed-integer linear program
Let $c \in \mathbb R^n$, $A \in \mathbb R^{m \times n}$, $b \in \mathbb R^m$, and $I \subseteq \{1,2,\ldots,n\}$. Consider the Mixed integer linear program (MILP)
$$
\begin{split}
f^* = &\max \; ...
2
votes
1
answer
270
views
What optimization problems have solutions with few nonzeros?
Consider the following optimization problem, with $n$ variables and $m$ linear constraints:
\begin{align}
\text{maximize} && c_1 x_1 + \cdots + c_n x_n &
\\
\text{subject to} && a_{...
1
vote
1
answer
517
views
Sparse, left-looking LU factorization
I'm trying to understand the left-looking LU factorization algorithm for sparse matrices, by reading T.A. Davis' book, and have trouble in one step (sorry for the specific question) about returning ...
2
votes
1
answer
454
views
why there is no relaxation method for Jacobi linear system iterative methods?
I found that the relaxation methods for solving linear system as an iterative sequence are derived from the Gauss-Seidel method and not from the Jacobi method. I understand that the Gauss-Seidel ...
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
1
answer
374
views
Sampling uniformly from the vertices of a polytope
I'm looking for a reference on how to sample uniformly (and preferably efficiently, elegantly, etc.) from the vertices of a polytope. I gather that enumerating vertices is hard. I also note the MO ...
2
votes
1
answer
3k
views
Eigenvalue and Eigenmatrix of a 3D Tensor - How to calculate it?
How to calculate easily the eigenmatrix of a 3D tensor.
I try immersing the tensor in a big matrix, in my case, the tensor is of nxnxn and I can build an n^2 x n^2 matrix that contains all the "...
1
vote
1
answer
330
views
How good is the LP relaxation?
Consider the optimization problem
\begin{align}
\max_{x\in\mathbb{R}^n}~c^Tx~, \text{ s.t. } Ax=b,~x_i\in\{0,1\}~\forall i
\end{align}where $c,b\in\mathbb{R}_{+}^n$ and $A\in\mathbb{R}_{+}^{n\times n}$...
5
votes
1
answer
213
views
Numerical instability of the axis-angle representation of rotations in 3D
Suppose that I have $1000$ pair of points where each pair consists of a point in $\mathbb{R}^3$ and its image after a rotation in $\mathrm{SO}(3)$ with some noise. I have used RANSAC to find the ...