Questions tagged [quadratic-programming]

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37 views

Implementation method selection for sparse constrained linear least squares or quadratic programming

I need to slove one optimization problem of quadratic programming. The number of optimization variables is about 16,000. The constraints include equality constraints and inequality constraints. I have ...
8
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1answer
261 views

Can this simple quadratic optimization problem be turned into a simple eigenvalue problem?

I'm interested in a type of problem on this form $$\min_{x} x^{T}Ax+x^{T}b \quad \text{s.t} \quad x^{T}x=1 $$ where $A$ is positive definite. As you can see, if it weren't for the $x^{T}b$ term in the ...
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0answers
51 views

Quadratic optimization with nonlinear vector term

I wish to minimize the quantity $$W=1/2x^TAx-x^Tg(y)$$ with respect to $x$ and $y$, which are vectors of unknowns. $A$ is a sparse square symmetric positive definite matrix and $g(y)$ is a vector with ...
5
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0answers
94 views

Generally quadratic convex problem with one non-convex term

How would you approach a standard convex quadratic problem with convex constraints but one non-convex term ? Say $|x|^{0.4}$. $$\min_x \frac{1}{2} x^{T}Qx + g^Tx + c^T \mathrm{sign}(x) |x|^{0.4} $$ ...
2
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1answer
91 views

Project to nearest point on convex polyhedron

I have a point $y \in \mathbb{R}^d$ and a convex polyhedron $\mathcal{P}$ given as the intersection of half-spaces: $$\mathcal{P} = \{x \in \mathbb{R}^d \mid a_1 \cdot x \le b_1, \dots, a_n \cdot x \...
3
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0answers
146 views

Automatically generate constraints for trajectory optimization

This is a follow up to my previous post here I'm interested in performing trajectory optimization from the problem mentioned in abov link. I want to supply the following as dynamical constraints to ...
1
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2answers
126 views

Solving a parameter estimation problem using trajectory optimization

This is a follow-up to my previous question here I've the following system of equations for studying information flow in the below graph, $$ \frac{d \phi}{dt} = -M^TDM\phi + \text{noise ...
4
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1answer
199 views

Which optimization method can be used to do the following?

I've the following system of equations for studying information flow in the below graph, $$ \frac{d \phi}{dt} = -M^TDM\phi + \text{noise effects} \hspace{1cm} (1)$$ Here, M is the incidence ...
2
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0answers
22 views

Barrier algorithm Gurobi and interior-point quadprog; what kind of matrices can it handle the best (sparse or dense, large or small problems)?

I am trying to solve a QP problem. Does anybody know the differences between the interior-point-convex algorithm of quadprog and the barrier method of Gurobi in terms which kind of matrices can the ...
5
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1answer
98 views

Complementary quadratic knapsack problem

The quadratic knapsack problem (QKP) $$\max_x x^TPx$$ $$\mathrm{s.t.}\;\;w^Tx\leq c,\; x\in\{0,1\}$$ where $P\geq0, w\geq0$ elementwise, is well studied and has existing solvers. My problem below ...
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1answer
969 views

Why am I getting this DCPError?

I'm trying to optimize a binary portfolio vector to be greater than a benchmark using CVXPY. ...
5
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0answers
105 views

Minimum of quadratic assignment (QAP) with convex objective

Suppose $A,B\succeq0$ and $C\in\mathbb R^{n\times n}$. I am hoping to solve an instance of the following optimization problem: $$ \min_{\textrm{permutation matrices }P} \mathrm{tr}(BP^\top AP+C^\top ...
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1answer
33 views

Minimize squared error of linear function

Let $M$ be a $m \times n$ matrix, $x$ a $n$-vector, $y$ a $m$-vector, and $\|\cdot\|_2$ represent the $L_2$ norm (i.e., Euclidean norm). Given $M,y$, the goal is to find $x$ that minimizes the ...
2
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1answer
86 views

Checking positive definiteness on a hyperplane

Is there a faster way to check whether $A\in\mathbb{R}^{n\times n}$ is positive definite on $b^{\bot}:=\{x\in \mathbb{R}^{n}: x\cdot b=0\}$ than ...
3
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1answer
63 views

Improve optimization speed for a set of similar problems: Quadratic programming with a warm start

I am repeatedly solving quadratic program, $x^T Q x$ with time dependent linear constraints $Ax=b_t$. Dimension of $x$ is around 10000 and there are around 50 constraints. I want to solve the ...
3
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1answer
292 views

What is the fastest way to solve Ax=b (subject to constraints and an absolute term)

I am trying to solve/optimize $Ax=b$ in the least squares sense subject to box constraints; a few (less than 5) equality/inequality constraints; and an absolute function penalty (or some other ...
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1answer
2k views

How to define the derivative for Scipy.Optimize.Minimize

I am trying to use scipy.optimize.minimize to minimise a quadratic objective function: $f(x) =x^\top Q x$. As a start, I have successfully implemented this using the built-in Nelder-Mead Simplex ...
1
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1answer
649 views

Reformulate a strictly convex QP problem containing absolute value term

Can the following strictly convex optimization problem be reformulated into a standard form that is also a strictly convex problem? $$\begin{align} &\text{Minimize }\frac{1}{2} x^T Q x + a^T x + ...
5
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0answers
154 views

Multi-matrix orthogonal basis problem

Suppose we are given a set of symmetric, positive definite matrices $A_1,A_2,\ldots,A_k\in\mathbb{R}^{n\times n}$. Is there any numerical method or reduction to a known problem (e.g. eigenvalue ...
3
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2answers
113 views

Approximating solutions to quadratic recurrence boundary value problem

Cross-posted from Math Stackexchange: https://math.stackexchange.com/questions/2421964/approximating-solutions-to-quadratic-recurrence I have a branching process problem that has been reduced to ...
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2answers
132 views

Factoring a quadratic function

I have a quadratic binary optimization problem of the form \begin{align} &\max x^TQx \cr &\text{subject to }x\in\mathcal{X}\subseteq\{0,1\}^n, \end{align} where $\mathcal{X}$ is the feasible ...
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1answer
155 views

How can I solve on a computer a large projection problem with redundant constraints?

This question is the essence of this one. After we remove all the cruft, we can recast it as follows: Problem: Given $b \in \mathbb{R}^n$, $C\in \mathbb{R}^{n\times m}$, and $g\in \mathrm{Range}(C^...
3
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1answer
75 views

Solving multiple least-square problems with the same constraints

The following least-square problem can be solved efficiently (e.g. using matlab's lsqlin): $$\vec{x}^*=\arg\min_\vec{x} ||C\vec{x}-\vec{t}||^2\,\ s.t.\ Ax \le \vec{b}$$ where the parameters of the ...
4
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2answers
903 views

Quadratic programs with rank deficient positive semidefinite matrices

Let $A$ be a $n\times n$ square symmetric matrix. In addition, $A\succeq0$ and $\mathrm{rank}(A)<n$. This means that all eigenvalues are non-negative, but also that there are some zero eigenvalues. ...
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0answers
53 views

energy computation for BVP with Dirichlet boundary conditions

I am solving quadratic minimization problem \begin{align} \min_{x}\ \frac{1}{2} x^T A x -b^T x, \end{align} where matrix A results from discretization of Laplacian by FEM method, subjected to ...
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0answers
54 views

minimization a quadratic form with linear constraints (Prospective method SMIC 74 method)

my problem is a ecuation i don't understand, I have no idea how to solve that, is a classic minimisation programme of quadratic form with linear constraints, here is the ecuation: $$\sum_{i,j}^n[P(i/...
2
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2answers
333 views

Approach to handle a quadratic constraint xy <= z

I have non-linear constraints like $ x_1x_2\leq x_3 $ where $ x_1,x_2,x_3\geq 0 $. The objective is linear, and all other constraints are linear, too. I know that I can transform the product as $ ...
0
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1answer
164 views

Optimization with Yalmip [closed]

I would like to solve in Matlab the following optimization problem $$\begin{array}{ll} \text{maximize} & \bigg\| \displaystyle\sum_{l=1}^{2}\alpha_l \int_{\tau_{m+l-1}}^{\alpha_1\tau_m+\alpha_2\...
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0answers
66 views

“Solution path” for quadratic program as regularizer changes

I am solving a quadratic program with regularization parameter $\alpha\geq0$ to get the solution to a problem of the form $$ p(\alpha):= \arg\min_{p\in\mathbb{R}^n}\ [\alpha(v^\top p)+f(p)], $$ where $...
1
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1answer
374 views

What is the fastest method for solving a quadratic programm repeatedly,( warmstarted)?

I would like to solve the following optimization problem \begin{align} \min_{x\in [0,1]^n} x^T p+ \frac{1}{2\lambda} x^T Q x \end{align} $Q$ is a positive semidefinite matrix. $\lambda>0$ is a ...
1
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0answers
50 views

Admissible box constraint for a quadratically constrained linear program [closed]

I am looking at a real-world resource allocation problem that is cast as a quadratically-constrained linear program of the form $$ \max\langle f,x\rangle $$ subject to $$ \begin{aligned} m \leq\,\, &...
1
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1answer
147 views

How to efficently solve: min $\sum_{ij}(a_{ij}x_{ij}^2 + b_{ij}x_{ij})$ s.t

I am trying to solve the following problem, where $a_{ij} \ge 0 \ \forall i,j$: \begin{align} \mbox{minimize}\quad & \sum_{i=1}^m\sum_{j=1}^n (a_{ij}x_{ij}^2 + b_{ij}x_{ij})\\ \mbox{subject to}\...
1
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1answer
194 views

Reformulation of optimization problem

I am looking for some helps concerning an optimization problem. I have an optimization problem defined on two sets $\mathcal{X}=\{x_i\}_{i=1}^n $ and $\mathcal{Y}=\{y_j\}_{j=1}^m $ and described as ...
6
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1answer
979 views

Algorithm for solving system of quadratic equations and linear equations

Let $x \in R^N$. From a Spectral Chebyshev collocation method, I have a system of quadratic and linear equations. Denote them, $$ x^T Q_i x + L_i^T x = 0 $$ and $$ A x = 0 $$ Furthermore, I know ...
4
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0answers
163 views

Eigenvalue-style optimization with quadratic constraints

Suppose $A\in\mathbb{R}^{n\times n}$ is symmetric and positive definite and that we have several symmetric matrices $B_i\in\mathbb{R}^{n\times n}$ that are low-rank and indefinite. I need an ...
5
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2answers
2k views

How to determine whether two cylinders intersect or not?

Considering any two cylinders, defined as: the center of their bottoms $A_i$, the radius of their bottom $R_i$, the unit vector $W_i$ of their axis direction, and the length $L_i$ of the cylinders, ...
1
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1answer
401 views

How to formulate variance minimization as a mixed integer quadratic program

I have a mixed integer quadratic problem and my objective function is as follows $$\arg \min \operatorname{Var}(f(x),g(x)) + \operatorname{Var}(c(x),d(x)) + \cdots$$ where $f$, $g$, $c$ $d$ are ...
0
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1answer
83 views

Can Variance be replaced by absolute value in this optimization problem

Initially I modeled my objective function as $$\arg \min \operatorname{Var}(f(x),g(x)) + \operatorname{Var}(c(x),d(x)) + \cdots$$ where $f$, $g$, $c$, $x$ are linear functions. To be able to solve ...
5
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1answer
4k views

Convex Optimization problem with sum of absolute value constraints

How to solve the optimization problem written below? $$\begin{align} &\operatorname{argmax}\limits_{a}\; a^T b - \frac{1}{2} a^T X a\\ &\text{subject to } \sum_i |a_i|=4,\; \sum_i a_i = 0 \...
2
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0answers
89 views

Disjunctive programming software

Can you advise me any kind of existing software that can help to solve the disjunctive programming problem? The problem is the following. We have unit 3D planes $\Pi_{1}, \ldots, \Pi_{N}$ (they are ...
2
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1answer
145 views

Solve $AX = B$ where $X^T X = C$

Is there a natural way to find the solution to $$AX = B, X^TX = C \enspace \text{?}$$ $X$ is a matrix and has a small number of rows, and $A$ is sparse. An approximate solution would be fine.
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2answers
1k views

Solving absolute value quadratic optimization problem

would you please help me to solve following problem $$x^*= \text{argmin}\ xLx^T+ |P^Tx|$$ $x$ is binary $P$ is a known vector (with positive and negative values) $L$ is Laplacian matrix I have ...
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2answers
211 views

Convex quadratic problem solver gives different answers?

I am pretty sure that the following variance objective function should be a convex quadratic problem. My objective function is as follows: $$ \text{argmin } \text{var }(X*L) \xi \geq 1, \text{ where }...
4
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1answer
1k views

Converting convex quadratic constraint to linear matrix inequality (LMI)

I have the quadratic programming problem in $x$ $$\text{Minimize}\;\; x^T\Sigma x$$ $$\hspace{15mm}\text{Subject to}\;\; p^Tx = \frac{1}{n}p^T\boldsymbol{1}$$ $$\hspace{25mm}\boldsymbol{1}^Tx=1$$ ...
2
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1answer
180 views

Solving the quadratic in the Fast Iterative Method

The Fast Iterative Method is a way of solving the Eikonal Equation on a discrete grid, similar to the Fast Marching Method discussed in another question here. The paper describes the overall ...
1
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1answer
496 views

Mixed-integer quadratic programming, state of art [closed]

I used Gurobi with a MIQP with 26 binary variables and 26*4 interaction term without any other constraint. The speed is very slow already.... I want to ask what is the state of art of MIQP solvers. ...
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3answers
2k views

Minimize quadratic form with equality constraints

I want to minimize function: $f(x) = x^T \cdot A \cdot x + b \cdot x$ given constraints: $B \cdot x = 0$. Here: $x$ is a vector ($x \in \mathbb{R}^n$), $A$ is a matrix of size $n \times n$, $b$ ...
1
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3answers
358 views

rank-deficient NNLS

I want to find the minimum-norm solution to a rank-deficient least-squares problem, subject to positivity constraints, e.g. $$\min_x\ \|x\|^2 \quad s.t.\quad Ax = b,\ x \geq 0$$ where $A$ is large, ...
2
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1answer
468 views

0,1 binary polynomial programming

Is there a mathematical optimization branch that explicitly tries to optimize this (type) problem? $$\eqalign{ & \min \cr & \sum\limits_{i = 1}^N {(J*s[i] + {J_1}*s[i]*s[i + 1] + {J_2}...
1
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1answer
784 views

How can a quadratic positive definite minimization be unbounded [closed]

I am minimising a diagonal quadratic matrix using CPLEX. All off diagonal elements are zero. It has 500 variables and 20 linear constraints plus each variable is constrained to be within 0 and 1 All ...