Questions tagged [nonlinear-optimization]
Nonlinear objectives, nonlinear constraints, non-convex objective, non-convex feasible region.
617
questions
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30
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Convexification of non-linear non-convex fractional function
I am trying to convert the non-convex, non-linear function, which is described here:
$$
\begin{equation}
Y_{(X_{1}, X_{2})} = \frac{X_{1}+X_{2}}{\alpha X_{1} + \beta X_{2}}
\end{equation}
$$
Where $X_{...
1
vote
0
answers
36
views
Gradient descent over the set of complex symmetric matrices
In the course of my research (somewhat related to compressive sensing), I am trying to determine a complex, symmetric matrix $L$ (i.e. $L = L^T$) through the following optimization formulation:
$$ \...
0
votes
1
answer
78
views
Optimality condition for strongly convex function under sparsity constraint
Let $f: \mathbb{R}^p \to \mathbb{R}$ be a $2s$-sparse strongly smooth, $2s$-sparse strongly convex and twice differentiable function. In other words, there exists positive constants $\alpha, L >0$ ...
0
votes
2
answers
319
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Any idea of solving an optimization problem with cubic constraints?
I have the following optimization problem with cubic constraints, which is hard to solve. Are there any ideas, or related references, of solving such a problem?
$$ \begin{array}{ll} \underset {y, z} {\...
0
votes
1
answer
69
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Clarification about this optimisation problem
Good morning everybody. First of all, I apologise to ask here the same question I asked on MSE three days ago, but I am in fact re-asking since I obtained no relevant advice. Perhaps I will hear some ...
0
votes
0
answers
32
views
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
44
views
How can we calculate the Euler-lagrange equations?
In this paper https://arxiv.org/pdf/1907.09605.pdf \
let $\Omega \subset \mathbb{R}^n$ with $n \geq 1$ be a bounded Lipschitz domain with boundary $\partial \Omega$, $f: \Omega \rightarrow \mathbb{R}$ ...
2
votes
1
answer
291
views
Is it possible to find an upper bound and a lower bound for $(f(\xi)-f(\tilde{\xi}))^T(\frac{\partial f}{\partial \xi}(\bar{\xi}))(\xi-\tilde{\xi})$?
For a system engineering problem I have to solve the problem below, but since I am not a mathematician, I am not sure if I have enough knowledge to solve it.
Problem definition: Let $f(\xi) \in \...
1
vote
1
answer
277
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Numerical estimation of partial derivatives of convolved functions when closed forms do not exist
Summary: Some peak functions are convolutions which may not have a closed form solution. A classical example can that of a Voigt which is a convolution of a Lorentzian and a Gaussian, followed by ...
1
vote
1
answer
113
views
Numerical partial differentiation of a convolution product with FFT
How can one numerically calculate the partial derivatives of a convolution function, particularly when the closed-form or analytical expressions of the derivatives are not readily available? I am ...
1
vote
1
answer
126
views
Bound the distance between two vectors on the probability simplex
Let $a,b$ be two vectors with strictly positive elements and $\delta = 1 - \frac{\langle a,b \rangle}{\|a\|\|b\|}$. Bound the following optimization problem as a function of $\delta$
$$\sup_{x>0} \...
2
votes
2
answers
287
views
Reference request on computational schemes for $\inf_{x\in\Omega^n}\sup_{y\in\mathbb R^n}F(x,y)$
Let $\Omega\subset \mathbb R^d$ be compact, $\rho$ be a density function on $\Omega$ and $p_1,\ldots, p_n\in (0,1)$ be weights satisfying $\int_{\Omega}\rho(z)dz=1=\sum_{k=1}^n p_k$. We consider the ...
4
votes
1
answer
241
views
Local maxima of the sum of Gaussian functions in *multiple dimensions* are always strict local maxima - prove/disprove/prove conditionally?
This is a follow up of the question in one dimension, that asked to show that the all the maxima of the sum of Gaussian
$$f_n(x):= \sum_{i=1}^{n}e^{-(x-x_i)^2}, x_1 < x_2 < \dots < x_n$$
are ...
1
vote
0
answers
58
views
Under which condition, such that all second-order critical points satisfy $\sum_j\cos(\theta_i-\theta_j)>0$ for all $i\in[n]$?
Consider the following non-convex function
$$E(\theta):=-\sum_{i,j}A_{ij}\cos(\theta_i-\theta_j)$$
where $A$ is a symmetric, diagonal-free matrix whose non-diagonal element are $\pm 1$. In other words,...
0
votes
0
answers
24
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How to control the angles of Kuramoto model by controlling its order parameter?
Consider Homogenous Kuramoto model in this paper. In theorem 3.1, the author derive condition on $A$ such that all second-order critical points of $E(\theta)$ are in two opposite quadrants, by saying ...
1
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0
answers
45
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How to derive a lower bound of a MinMax inequality?
Let $x_5,\cdots,x_n\in[0,\alpha]\cup[-\pi,\alpha-\pi]$ where $\alpha$ is a fixed angle $\in(0,\pi/2)$.
The goal
For a fixed $(A_{ij})_{1\leq i\leq 4,5\leq j\leq n}\in\{-1,+1\}$, verify whether it ...
0
votes
0
answers
30
views
Efficient algorithms to find the global minimum of a non-convex quadratically-constrained quadratic program
I am working on a problem involving a non-convex quadratically-constrained quadratic program and am seeking efficient algorithms to find its global minimum. The problem is structured as follows:
Fix ...
2
votes
1
answer
347
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A "nice" (but non-definite) quadratic programme
For integers $n\geq k>0$, let $f$ be the following quadratic form:
$$f(x_1,\ldots,x_n)=\sum_{i=1}^n\sum_{j=0}^{k-1}x_ix_{i+j\bmod n}.$$
Is it true that the minimum of $f$ over the unit simplex is ...
1
vote
1
answer
86
views
How to interpret the vector fields $F_p(x,u,Du)$ in a Lagrangian optimization problem
Let $\Omega$ be an open bounded subset of $\mathbb{R}^n$ with $C^1$ boundary. Let
$$
\begin{matrix}
F: \mathbb{R}^n \times \mathbb{R}^N \times \mathbb{R}^{nN} \to \mathbb{R},& \\
(x,z,p) \mapsto F(...
2
votes
1
answer
300
views
How to solve an optimization problem whose optimization variable is a function?
I would like to find an optimal probability density function (PDF) $f$. Given $b$,
$$ \begin{array}{ll} \underset {f} {\text{minimize}} & C \\ \text{subject to} & 1 + \frac{b}{x} \displaystyle\...
0
votes
0
answers
38
views
Seeking help with a matrix optimization problem involving matrix exponentiation
I'm working on an optimization problem where I need to find matrices $P$, $Q$, and $C$ that minimize the norm of the difference between a given matrix $A$ and another matrix defined as $e^{P(Q + Q^T - ...
0
votes
0
answers
146
views
Do we have tetration uniqueness by $ A = \inf \sum_n a_n^2 $?
Let $f$ be a real analytic (on at least $|x|<2$) and real solution of the functional equation $f(0) = 1,f(x+1) = \exp(f(x))$. For the existence of such $f$, see here.
Then
$$
f(x) = \sum_n a_n x^n ;...
3
votes
3
answers
455
views
Looking for a very particular kind of non-convex functions
I want some examples (hopefully parametric families!) of non-convex functions which satisfy the following properties simultaneously,
It should be at least twice differentiable.
It should have a ...
0
votes
1
answer
71
views
Optimization: Determine the categorical pmf that maximizes the objective function
Let $T$ denote a $J$-component categorical random variable with pmf
$$
\mathsf P(T=t_j)=w_j,\quad j=1,2,\dots,J,
$$
where $t_j\in[0,t_\max]$, $t_\max>0$.
I came across a problem that seeks to ...
4
votes
1
answer
154
views
Gap to fill in the Aubin–Ekeland proof of the mountain-pass theorem
Working through the proof of the mountain-pass theorem given in Applied Nonlinear Analysis by Aubin & Ekeland, at what seems to be a critical point of the proof (the top of page 274) they refer to ...
0
votes
1
answer
475
views
How do I get an analytical solution to this nonlinear equation?
I posted this question over on Math Stack Exchange (link), but have not received a response. I'm wondering if it's too complicated for that audience, so I'm posting it here in the hopes that someone ...
0
votes
1
answer
104
views
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 ...
0
votes
0
answers
92
views
Primal optimal attained implies dual optimal attained
Given some optimization problem
$$\min_{x \in S \subset \mathbb{R}^n} f_0(x) \quad \text{s.t.} \quad f_i(x) \leq 0, \quad 1\leq i\leq m$$
we can find the dual problem
$$\max_{\lambda\in\mathbb{R}^m} g(...
3
votes
1
answer
157
views
Numerical scheme for convex optimization
Given $(e_n)_{-N\le n\le N}\in\mathbb R^{2N+1}$ and $-1<x<1$, solve
\begin{eqnarray}
&&\max_{(q_n)_{-N\le n\le N}\in\mathbb R^{2N+1}_+}~ \sum_{n=-N}^N (e_n-\log(q_n))q_n \\
\mbox{s.t.} &...
0
votes
0
answers
25
views
Which penalization works for this optimisation problem?
Let $m,n$ be given integers. Set $K:=[0,1]^{mn}$ and define the function $L:K\times\mathbb R_+^m\times\mathbb R_+^n\to\mathbb R$ as follows : for $z=(z_{i,j})\in K$, $a=(a_i)\in\mathbb R_+^m$, $b=(...
2
votes
1
answer
155
views
Can we say this nonlinear integer programming problem is NP-hard?
I was wondering if the following nonlinear integer programming problem is NP-hard or not.
$$\max_{x_i \in \{0,1\}} \frac{\sum_{i=1}^{n}a_i x_i}{\sqrt{\sum_{i=1}^{n}b_i x_i}}$$
such that $\sum_{i=1}^{n}...
0
votes
1
answer
121
views
How to integrate an indicator function/constraint into the cost function of a linear program?
I have a mathematical model $P$ for which I optimize two cost functions say $F_1$ and $F_2$ subject to a set of constraints $C1$–$C10$.
In $F_2$, I want it to be included only when its expression ...
4
votes
2
answers
630
views
Difference between Chebyshev first and second degree iterative methods
Consider linear equation $Au = f$.
We want to solve it with iterative method (assuming $A$ is good).
First order iterative method is:
$$
u^{k+1} = u^k - \alpha_{k+1}(Au^k - f),
$$
The second degree ...
0
votes
0
answers
72
views
Error bound for stochastic gradient descent method
To solve an optimization problem $\min_x G(x)$ using standard stochastic gradient descent method, we let $x_0$ be the initial point and $x_k$ be the $k$-th point such that
\begin{equation}
x_k = x_{k-...
4
votes
1
answer
217
views
Equivalence of bounded gradient flow solutions and uniformly bounded gradient descent trajectories for definable functions
I am reading paper [1] by C. Josz regarding the global convergence of the gradient method. The main result is the following:
$\textbf{Theorem}$: For a definable differentiable function $f : \mathbb{R}^...
1
vote
1
answer
163
views
Maximization of $\ell^2$-norm
Consider for $r,c>0$ the set
$$X_{r,c}=\{x \in \ell^1(\mathbb{N}) \mid \|x\|_1=r,\, \forall i \in \mathbb{N}: |x_i|<c\}.$$
Then I can show that $\inf_{x \in X_{r,c}} \|x\|_2 = 0.$
But is it ...
2
votes
2
answers
73
views
Reference for article that introduces and motivates different notions of subdifferentials
I saw a tutorial/expository journal article a while ago that focused on introducing intuitively different notions of subdifferentials appropriate for general nonlinear optimization. I forgot the ...
4
votes
1
answer
799
views
Lagrange-Newton minimization and initial value for the Lagrange multipliers
Short version. How to choose the initial values for the Lagrange multipliers in the Lagrange-Newton
equality-constraint minimization method?
Introduction. The problem to solve is
\begin{equation}
\...
0
votes
0
answers
33
views
Solving optimization problem restricted to non-convex subset
I have two continuous random variables that have pdfs with respect to the Lebesgue measure $p_{-1}(x), p_1(x)$.
Let $m(x) := \frac{p_{-1}(x)+p_1(x)}{2}$ be a mixture of these two distributions.
Let $B(...
1
vote
0
answers
80
views
Positive semidefinite maximum principle
Let $K\in\{\mathbb{R},\mathbb{C},\mathbb{H}\}$. Let $\mu$ be a Borel probability measure on $M_n(K)$ supported on a compact set $C$ of positive semidefinite matrices with $\mathbf{0}\not\in C$. ...
0
votes
0
answers
26
views
Convergence bound for zero-order optimization method
I would like to understand the error bound for a particular zero-order optimization method: (stochastic) difference method.
To solve an nonsmooth optimization problem $min_x G(x)$ where $G$ is only a ...
1
vote
1
answer
81
views
optimization over moving domains
Let $A, B$ be Banach spaces, and for any $a\in A$, $B_a\in B$ is a measurable subset. Consider the following optimization problem:
$$L(a)=\inf_{b\in B_a}\ell(b),$$
where $\ell(b)$ is a infinite-times ...
0
votes
1
answer
139
views
nonlinear equation problem
Can you please help me solve the following nonlinear equation to determine the value of the vector $z$ :
$$
\boldsymbol{a}=\boldsymbol{z}^{2} \odot \boldsymbol{K}*\boldsymbol{z}^{-1}$$
Where:
$\...
-1
votes
1
answer
703
views
How can I deploy a CG-Steihaug algorithm for trust region sub-problem solving?
I'm studying various optimization methods and on this occasion, I'm trying to tackle the Trust Region Problem by solving the sub-region problem with the Steihaug-CG algorithm in Python. I'm using the ...
1
vote
0
answers
53
views
LICQ vs MFCQ who is stronger [closed]
I want to ask you which constraint is stronger: MFCQ or LICQ.
2
votes
1
answer
143
views
Optimization over permutation
The Problem
This is the problem I am working on: Given a set $X = \{x_1, x_2, \cdots , x_n\}$ in a metric space, find an optimal ordering $\pi : X \rightarrow X$ that maximizes the following objective ...
7
votes
3
answers
679
views
How to solve such an optimization problem
I encounter the following optimization problem, but I can't solve it.
Given $N$ variables satisfying $0 \leq x_1 \leq x_2 \leq x_3 \leq ... \leq x_N \leq 1$ and an integer $K$ no large than $N$, find ...
2
votes
1
answer
145
views
Argmax of a function of $n$ variables under linear constraint
(I start by saying that the tags are probably not accurate but I didn't know what to put, so if someone knows what I could tag this question with, let me know in the comments and I'll provide to edit ...
1
vote
1
answer
128
views
Maximal entropy distribution on three variables knowing its marginals on any two
Observation 0: Given a finite set $X$, the probability distribution on $X$ with highest entropy is the uniform one. This is well known.
Observation 1: Given two finite sets $X,Y$ and two probability ...
3
votes
1
answer
75
views
Detecting linear operator from actions of powers on subspace
Say I have a sequence of linear operators $A_1,...,A_n$ on a (real) vector space $V_1$. I suspect that there's a second vector space $V_2$, and an operator $A$ on $V_1\oplus V_2$, such that $A_i=(\...