For questions about optimizing an objective function that is quadratic in its input variables. This could include questions about implementing solver methods or choosing the right solver for a given problem.

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### Is solving QP easier than a QCQP with linear objective?

Is solving a $QP$ (i.e.: quadratic program, hence a quadratic objective function with linear constraints) easier than solving a $QCQP$ (ie.: quadratic constrained quadratic problem) with linear ...
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### 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 ...
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### 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 ...
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### Why am I getting this DCPError?

I'm trying to optimize a binary portfolio vector to be greater than a benchmark using CVXPY. ...
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Suppose $A,B\succeq0$ and $C\in\mathbb R^{n\times n}$. I am hoping to solve an instance of the following optimization problem: $$\min_{\textrm{permutation matrices }P} \mathrm{tr}(BP^\top AP+C^\top ... 1answer 801 views ### Reformulate a strictly convex QP problem containing absolute value term Can the following strictly convex optimization problem be reformulated into a standard form that is also a strictly convex problem?$$\begin{align} &\text{Minimize }\frac{1}{2} x^T Q x + a^T x + ...
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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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### 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 ...
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### 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 ...
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### 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 ...
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### Solving a least squares problem with linear constraints in Python

I need to solve \begin{alignat}{1} & \min_{x}\|Ax - b\|^2_{2}, \\ \mathrm{s.t.} & \quad\sum_{i}x_{i} = 1, \\ & \quad x_{i} \geq 0, \quad \forall{i}. \end{alignat} I think it is a ...
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### Modeling a quadratic constraint with a linear expression

In a problem I am trying to model with a MIP program, the following scenario occurs: I am given binary variables $x_1,\ldots,x_n$ and $y_1,\ldots,y_n$ which can really be regarded as $n$-vectors. ...
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### Converting convex quadratic constraint to linear matrix inequality (LMI)

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