# Questions tagged [non-convex-optimization]

The non-convex-optimization tag has no usage guidance.

53
questions

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### Generalizations of Berge's maximum theorem

I have a parameterized optimization problem
\begin{eqnarray}
\max_{x\in D(\theta)} f(x,\theta).
\end{eqnarray}
Assumptions of the standard Berge's maximum theorem are satisfied, so the value function $...

1
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0
answers

61
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### Under which condition, such that all second-order critical points satisfy $\sum_j\cos(\theta_i-\theta_j)>0$ for all $i\in[n]$?

Consider the following non-convex function
$$E(\theta):=-\sum_{i,j}A_{ij}\cos(\theta_i-\theta_j)$$
where $A$ is a symmetric, diagonal-free matrix whose non-diagonal element are $\pm 1$. In other words,...

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0
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33
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### Efficient algorithms to find the global minimum of a non-convex quadratically-constrained quadratic program

I am working on a problem involving a non-convex quadratically-constrained quadratic program and am seeking efficient algorithms to find its global minimum. The problem is structured as follows:
Fix ...

4
votes

2
answers

192
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### Minimal norm of Fréchet subdifferential for function Lipschitz over its domain

Let $f:\mathbb{R}^n\rightarrow\mathbb{R}\cup\{+\infty\}$ be an extended real-valued function that is proper, lower semicontinuous, and Lipschitz continuous over its domain $\newcommand{\dom}{\text{dom}...

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0
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85
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### How to solve mckp (multiple-choice knapsack problem) problem with non-linear constraint

How to solve the below optimization problem? $P$ is a probability matrix, $0\le P_{ij}\le 1$. Are there any developed tools to solve this? Thanks a lot.
\begin{equation*}
\begin{aligned}
&\...

1
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0
answers

107
views

### Maximisation of a convex (quadratic) function

This post is a continuation of A variant of (discrete) optimal transport problem
For $\alpha=(\alpha_1,\ldots,\alpha_m)\subset\mathbb R^m_+$, $\beta=(\beta_1,\ldots,\beta_n)\subset\mathbb R^n_+$ and $...

0
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0
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55
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### Trying to transform a minimization problem to a saddle point problem for the primal–dual algorithm

I’m reading about a problem, and the author goes from a classical minimization problem to a saddle point problem in order to perform a primal–dual algorithm on it [1].
However, It’s my first problem ...

0
votes

1
answer

123
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### An optimization problem with variables on the exponential of a complex number

$$\min_t \quad\operatorname{Re} \sum\limits_{i = 1}^N {\left( {{e^{ - j2\pi {f_i}t}}{r_i}} \right)}, $$where $\operatorname{Re}$ refers to get the real part of a complex number, $\{f_i\}$ is an ...

1
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1
answer

398
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### Is non-convex optimisation really in NP class?

Crossposted on Mathematics SE
I've seen in many optimisation papers the statement that general non-convex optimisation problem is NP-hard. If we assume that non-convex optimisation is in NP class, it ...

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135
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### Can I solve this quadratic program "fast"?

We are given a matrix $D \in \mathbb{Z}^{C \times C}$ of non-negative entries, an integer $k \geq 1$ and we need to maximize the quadratic form $x^T D x$ under some simple constraints. For all ...

4
votes

2
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137
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### $O(n^{2-\epsilon})$ bound on choosing $n$ points on the hypersphere to maximize $\pm 1$ weighted sum of their $\binom{n}{2}$ inner products

Given $n,d\in\mathbb{N}, n\gg d$, I'm looking for a bound on the maximum (or minimum) expected value of the following game:
Draw a vector $\epsilon\in\{\pm 1\}^{\binom{n}{2}}$, uniformly at random. ...

1
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0
answers

70
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### Minimize smooth function $(x,y) \to f(x,y)$ subject to $x \perp y$

Let $V$ be a finite-dimensional real vector space (e.g space of $m \times n$ real matrices equiped with Hilbert-Schmidt inner product $(A,B) \to \mathrm{tr}(AB^\top)$, and let $f:V^2 \to \mathbb R$, $(...

0
votes

1
answer

79
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### PCA, relation between the error and variance

As is known, the rank-1 PCA aims to solve the following optimization problem
$$\min_{x\in\mathbb{R}^d}\quad -x^T \Sigma x\quad\quad\quad \text{s.t.}\quad \Vert x\Vert_{2}=1,$$
where $\Sigma\in\mathbb{...

2
votes

0
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420
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### Global minimum of sum of a non-convex and convex function, where minima of the non-convex function can be found

I'm interested in finding $\arg\min_{x \in X} (f(x) + \lVert x\rVert_2^2)$ where $X$ is a $[0,1]^n$, $f$ is Lipschitz but non-convex and we already have a procedure to find some $x^* \in \arg\min_{x\...

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1
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155
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### Prove zero slope point is global maximum for constrained function with binomials. Without restriction, objective function is non-concave

How to prove the zero slope point is a global maximum in this non-concave program for a function with binomials?
I need to find the (global) maximum of the following constrained problem:
$$\max_{CAP} \...

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0
answers

108
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### Minimising kurtosis (non-convex). Can I use algebraic geometry or alternate methods to show uniqueness of a particular solution?

I consider a weighted sum of $n$ identically-distributed correlated random variables. The weights in the sum, $w_i$ for $i=1, 2,...,n$, satisfy $w_i>=0$ and $\sum_{i=1}^{n}w_i=1$. I am ...

3
votes

1
answer

229
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### Nonconvex optimization with linear constraints

Which algorithms are suitable for solving problems of the form
$$
\min_x \lbrace f(x) \; | \; Ax \leq b \rbrace
$$
with nonconvex, differentiable obfective $f$. Unfortunately, $f$ cannot be assumed to ...

1
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0
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484
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### Minimizing the Frobenius norm of a quadratic matrix expression

Given matrices $R \in \mathbb R^{m \times n}$ and $Y \in \mathbb R^{p \times n}$, where $R$ is full rank, how can I solve the following optimization problems?
$$\min_{X \in \mathbb R^{p \times m}} \| ...

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55
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### Why the result of the non-convex optimization problem will be farther and farther away from the optimal

When I try to solve a optimization problem by Riemannian stochastic variance reduced gradient algorithm(RSVRG), the formulation of problem like $\frac{1}{N}\sum_{i=1}^Nf_i(x)$ and $f_i(x)$ is a non-...

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0
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63
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### (Iterative?) Solutions to a certain quadratic program with non-convex constraints

Let $y\in\mathbb{R}^m$, $\tau\in\mathbb{R}$ and $X\in\mathbb{R}^{m\times n}$, with $\tau>0$
I would like to efficiently solve the following problem:
Problem 1
Choose $\alpha,z\in\mathbb{R}^m,\beta\...

0
votes

0
answers

300
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### Convergence of heavy-ball method for non-convex optimization

The heavy-ball method (also called gradient descent with momentum) is commonly used in optimization. The update rule can be written as:
$$x_{t+1}=x_t-\eta\nabla f(x_t)-\beta (x_t-x_{t-1})$$
Suppose $\...

1
vote

1
answer

735
views

### Hardness of concave minimization problem

I have an optimization problem $\underset{x}{\min} ~ c(x) - k \cdot x$ where $c(x)$ is a non-decreasing concave function with $c(0) = 0$, $x \in C \subseteq \mathbb{R}^d_{\geq 0}$. By non-decreasing, ...

2
votes

0
answers

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### Variational forms of non-convex functions

I am trying to understand what kind of variational forms exist for non-convex functions. Alternatively, are there conjugate forms which attain strong duality? For a non-convex function $f$, I am ...

3
votes

0
answers

164
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### Necessary optimality condition for quadratic programming: a solution of a constrained QAP is a solution of a LP

I have a concern about a result given by Murty in [1] and also written by Floudas and Visweswaran in [2]
They consider a QP:
\begin{array}{ll}{\min _{x} Q(x)} & {=c^{T} x+\frac{1}{2} x^{T} D ...

1
vote

1
answer

344
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### A quadratic program with non-negativity constraints

Is there any closed form solution for the optimal value of the folowing optimization problem?
$$\begin{array}{ll} \text{minimize} & (\mathbf{x} - \mathbf{y})^{\mathrm{T}}\mathbf{B}(\mathbf{x} - \...

6
votes

1
answer

739
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### 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 ...

5
votes

1
answer

1k
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### Solving a linear program, but over the unit sphere

I want to solve a linear program but with a subset of the variables taken from a unit sphere.
That is, given fixed $\textbf{c} \in \mathbb{R}^{n}$, $\textbf{A} \in \mathbb{R}^{m \times (n+k)}$,
I want ...

2
votes

0
answers

229
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### Quartic optimization problem over the unit Euclidean sphere

I want to solve following optimization problem in $x \in \mathbb R^n$.
$$\begin{array}{ll} \text{maximize} & \displaystyle\sum_i(x M_i x^T)^2\\ \text{subject to} & \|x\|_2 = 1\end{array}$$
...

2
votes

0
answers

76
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### Solving Mixed-Integer Non-Linear Optimization Problem

I would like to solve the following optimization problem:
\begin{array}{ll}
\underset{x_{i}\geq0,\, \pi_{i}\in\{0,1\}}{\text{minimize}} & \displaystyle\sum_{i=1}^n x_i\\
\text{subject to} & ...

3
votes

2
answers

326
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### 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 ...

7
votes

2
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538
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### Proving an infinite norm minimization problem has finite support (non-convex p-norms)

Consider an optimization problem over infinite variables:
$$
\begin{align}
\min_{x}~& {\left\lVert{x}\right\rVert }_p
\\
\text{s.t}~& \left\langle x, a_n\right\rangle \ge 1~,~\forall n=1,\...

5
votes

1
answer

409
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### Optimizing a multivariate symmetric (permutation-invariant) function

Let $\ell$ and $d$ be two integers such that $\ell \le d$.
I would like to find the global maxima of the following symmetric function $f\colon (0,1]^n \to \mathbb{R}$,
$$f(x_1, \ldots, x_n) := \sum_{\...

4
votes

2
answers

5k
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### Maximizing a convex function with a convex constraint

Given a convex function $f : \mathbb{R}^n \to [0,\infty)$, the objective is to find the farthest point in the level set $\left\lbrace x \in \mathbb{R}^n \mid f(x) \leq 1\right\rbrace$ (Assuming that ...

2
votes

1
answer

102
views

### Linear optimization with one positive definite quadratic equality condition in P?

I have the following minimization problem in $z \in \mathbb R^n$, which contains $x_1, \dots, x_t, y \in \mathbb R$.
$$\begin{array}{ll} \text{minimize} & y\\ \text{subject to} & xQx'= y\\ &...

0
votes

0
answers

174
views

### non-convex optimization with constraint

I have a special non-convex optimization problem:
$\min / \max \ f(x) + g(x) + h(x)$,
subject to $| g(x) - h(x)| < \varepsilon$,
where $f(x)$ is non-convex, but both $g(x)$ and $h(x)$ are ...

1
vote

1
answer

496
views

### Maximizing quadratic form subject to inequality constraints [closed]

Given a $n \times n$ symmetric matrix $\rm S$, solve the optimization problem in $n \times k$ (where $n \geq k$) matrix $\rm X$
$$\begin{array}{ll} \text{maximize} & \mbox{tr} \left( \mathrm X^\...

7
votes

2
answers

734
views

### Eigenvalue problem with two quadratic constraints

I would like to solve the following problem:
$$\begin{array}{ll} \text{minimize} & \mathbf{x}^T \mathbf{A} \mathbf{x}\\ \text{subject to} & \mathbf{x}^T\mathbf{B}\mathbf{x} = 0\\ & \...

3
votes

1
answer

122
views

### Why to multiply the penalty by $n$ in the penalized least squares and likelihood?

In the SCAD paper by Fan and Li (2001), there exist two forms of penalized least squares as follows:
$$\frac{1}{2}\left \| y-X\beta \right \|^2+\lambda \sum_{j=1}^{d}p_j (\left | \beta _j \right |),$$
...

2
votes

1
answer

512
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### Are there any solvers to Chance Constrained Programming Problems

I'm trying to solve a chance constrained programming (CCP) problem
$\min_x f_0(x, \xi), \text{ such that } \mathbb{P} ( f_i(x, \xi) \ge \alpha_i ) \le \epsilon_i, \text{ where } i = 1,2,\cdots, m$
...

6
votes

2
answers

442
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### Maximize the determinant of Boolean combinations of positive definite matrices

I have the following optimization problem.
$$\begin{array}{ll} \text{maximize} & \det \left(\sum^n_{i=1}z_i W_i \right)\\ \text{subject to} & \sum_{i=1}^n z_i = N\\ & z_i
\in \{0,1\}\end{...

4
votes

1
answer

4k
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### Can you give me good examples of non-convex functions that are problematic for optimization?

I want to test my extended gradient descent algorithm, whose aim is to handle non-convex problems better. Can you give me some examples of non-convex functions that are hard to minimize via gradient ...

1
vote

0
answers

405
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### Is this QCQP convex or nonconvex?

\begin{equation}
\begin{split}
\min_{x\in \mathbb{R}^n}\:f(x)=(1/2)x^{T}Q_0x+c_0^T x
\end{split}
\end{equation}
s.t.
$$
g_i(x)=\frac{1}{2}x^T Q_ix-lmax_i\leq0,i\in\{1,...,m/2\}
$$
$$
g_i(x)=\frac{...

7
votes

2
answers

4k
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### Quadratically constrained linear program (QCLP) over $x$ with the linear constraint $x = Az$

I have a problem that looks very much like a norm-constrained linear program, but with an extra constraint that is unusual for me. The problem is the following. Given a matrix $A$ and a vector $w$,
$$...

15
votes

2
answers

6k
views

### Linearly constrained eigenvalue problem

Suppose I'd like to:
\begin{align}
\mathop{\text{min}}_\mathbf{x} && \mathbf{x}^T\mathbf{A}\mathbf{x} \\
\text{subject to:} && \mathbf{x}^T \mathbf{M} \mathbf{x} = 1\\
&& \...

5
votes

1
answer

2k
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### Maximizing quadratic form on the hypercube

I want to maximize a quadratic form $\mathbf x^T\mathbf Q\mathbf x$ and also want to find out which vector $\mathbf x$ maximizes the quadratic form when
$\mathbf Q$ is an $n\times n$ positive ...

3
votes

1
answer

845
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### Nonconvex optimization problem

I have a nonconvex optimization problem with a linear objective function, a set of linear constraints and a set of nonlinear, non-convex constraints. Is this problem NP-hard? If so, how can I prove ...

3
votes

1
answer

589
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### Is the feasibility of a system of non-convex quadratic equations and inequations decidable?

I would like to know whether the following problem is decidable.
Given the following system in $x \in [0,1]^n$
$$x^T Q_i x + r_i = 0 \mbox{ for } i = 1, ..., k$$
$$x^T Q_j x + r_j \neq 0 \mbox{ ...

2
votes

1
answer

283
views

### Non-convex quadratic optimization

I would like to optimize the following system:
$$\min_{q,\|q\|=1} \sum_i^n |q^T M_i q|$$
More details:
the size of the unknown vector $q$ is $4 \times 1$,
$M_i$ is a matrix of size $4\times 4$. It ...

1
vote

1
answer

652
views

### A non-convex quadratically constrained quadratic program

$$\begin{array}{ll} \text{minimize} & \beta^{T} A \beta\\ \text{subject to} & \beta^{T} C \beta=1\\ & \beta \geqslant 0\end{array}$$
where $A, C\in \mathbb{R}^{M\times M}$ and $\beta \in ...

2
votes

1
answer

1k
views

### Can one maximize the spectral norm of a matrix via semidefinite programming?

Consider the following optimization problem:
Maximize $\|X\|_2$, subject to $X$ being Hermitian (or symmetric) and a bunch of semidefinite constraints on $X$. Here, $\|X\|_2$ is the spectral norm of ...