A non-linear optimization problem includes an objective function (to be minimized or maximized) and some number of equality and/or inequality constraints where the objective or some of the constraints are non-linear. Use this tag for questions related to the theory of solving such problems or for ...

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3
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1answer
45 views

How to find the minimal value of this function under such constraint

$f(x,y)=x-\sqrt{y-x^2}$ with $a<x<b$ and $x^2<y<c*x-d$. What I did is, first take partial derivative at $x$ and $y$ respectively, however, there is no critical point because fy is always ...
3
votes
2answers
131 views

Singular Values of Matrix as Optimization Problem

Assume that $A$ is a positive semidefinite symmetric matrix. It is known that $$\max_{||y||\leq1} \quad y^TAy$$ Has an analytical solution which is the maximum eigenvalue of $A$. This isn't hard ...
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0answers
37 views

Complex Non-liner First order ODE problem

Good day people I am modelling a "water bottle rocket" using basic Continuum Mechanics. I have found a equation describing the acceleration of the rocket. I need to integrate this function to find ...
2
votes
1answer
100 views

Extremum of functional of a complex function

consider functional $E$ defined by $$E[z]=\int F(x,z(x))dx$$ where $F$ is a complex-valued nonlinear function. How can we find the function $z(x)$ so that $$G=|E|^2=EE^*=\iint ...
1
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1answer
43 views

The most optimal way to solve this set of non-linear equations in high dimensions

So I have a series of non-linear equations which I wish to solve as fast as possible, to illustrate for the case of $n = 4$, I have the following equations: \begin{gather*} ...
0
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1answer
42 views

Is it possible to convert into linear programming problem

I have a problem of the form $$\sup_{x\in\Bbb{C}^n}\left\{\frac{\|Ax\|_\infty}{\|Bx\|_\infty}\right\}$$ where $A$, $B$ are matrices with different number of rows and $x$ is an $n$ dimensional vector. ...
0
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0answers
38 views

Combinations of Convex Functions

I'm looking at the following non-linear optimization theory problem: Let $\gamma$ be a monotone nondecreasing function of a single variable (that is, $\gamma(r) \le \gamma(r')$ for $r' > r$), ...
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0answers
39 views

Proofs involving closedness of compositions of mappings.

I've feel like I've gotten myself in over my head in a non-linear optimization course I seem to lack the mathematical maturity for(I'm an undergrad, I've taken the calc series, Intro to differential ...
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0answers
27 views

Implementing a projection with KL-divergence

I want to implement the following and I am looking for an easy/fast way to implement it(the programming language does not matter). Assume that $p(\mathbf{x})$ is a proper probability distribution and ...
2
votes
1answer
36 views

Conceptual Understanding of Non-Linear Optimization Problem

I'm in non-linear optimization, and I'm having trouble wrapping my head around what this problem is asking me for. If anyone could help with a conceptual explanation (not an answer!), it'd be greatly ...
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0answers
23 views

complexity of an optimization problem

Consider $n$ variables $x_1, \cdots, x_n$ with the constraint $\sum_{i=1}^n x_i=1$ and $x_i\geq 0$. I want to minimize $\vec{a}^T (I-\alpha A(\vec{x}))^{-1} \vec{b}$, where $\vec{a}$ and ...
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0answers
65 views

How to minimise an objective function which is not a direct function of the decision variable?

I have a problem with partitioning a water network by closing some pipes. I use some graph theory techniques to find some candidate pipes to close; but to select which pipes among them to close (my ...
1
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1answer
53 views

Prove that a multivariable function doesn't have global extremes

So my question is actually this. Say I have a function $F:\mathbb R^2\to\mathbb R$. If I find all the potential local extremes by finding the roots of the partial derivatives and I find that only one ...
0
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3answers
68 views

shortest distance between two points [duplicate]

I could not solve the following problem, Please help me, Let $P_1=(x_1,y_1)$ and $P_2=(x_2,y_2)$ be two given points. find the third points $P_3=(x_3,y_3)$ such that $d_1=d_2$ is minimized, where ...
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0answers
48 views

is there any infinity norm bound to simplify this

I have a problem of the form $$\sup_{x\in\Bbb{C}^n}\left\{\frac{\|Ax\|_\infty}{\|Bx\|_\infty}\right\}$$ where $A$, $B$ are matrices with different number of rows and $x$ is an $n$ dimensional vector. ...
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2answers
37 views

Constraints in optimization; redundant hardness?

This is not an accurate mathematical problem, and rather a philosophical and ambitious question. As far as I know, unconstrained problems are easier than constrained problems; right? This is mostly ...
3
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1answer
82 views

Does having a zero eigenvalue preclude a matrix from being indefinite?

If a $3\times3$ matrix has a positive eigenvalue, a negative eigenvalue, and a zero eigenvalue, is it then, by definition, indefinite? I think so, since the matrix has both a positive and a negative ...
0
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1answer
262 views

Converting Non-linear Programming Problem from Maximization to Minimization

I have a non-linear maximization problem and I want to convert it to be a minimization problem, can I do so by multiplying it by a negative sign, or is that wrong; and if that is wrong what should I ...
2
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2answers
204 views

What change of variables, if any, transforms this nonconvex problem into a convex one?

I'm looking for a convex reformulation, if any exists, of the following minimisation problem: Let $A$ be a symmetric, positive definite $n \times n$ matrix, and $b \in \mathbb{R}^n$. Minimise ...
1
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0answers
37 views

Effect of approximating a non-differentiable function on optimisation of minimisation

I am looking at a problem of constrained minimization, where the function to be minimized contains the Heaviside function, and as such is not twice continuously differentiable. My question is what ...
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0answers
34 views

Representing a 2D function as a sum of rectangles of arbitrary shape and orientation

Suppose I am given a non-negative function $f(x,y)$ defined for $x \in [0,1]$ and $y \in [0,1]$. I'd like to represent this function as a weighted sum $w_i$ of a small number of rectangular apertures. ...
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0answers
648 views

Significant improvement when I use lsqnonlin function with wrong sized X

I was trying to solve a nonlinear least-square optimization problem using matlab function lsqnonlin with default algorithm trust-region-reflective. Let the optimization problem be "minimize ...
1
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2answers
495 views

How to find roots of a non linear multivariable equation using numerical methods

I started a course in linear algebra and numerical methods but I couldn't understand how can we numerically find roots of a nonlinear multivariable equation. f: Rn -> R Find f(x)=0 where x is ...
2
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1answer
61 views

Initialization of Limited-memory BFGS (using libLBFGS)

I am using the package libLBFGS in order to minimize an objective function, for which the first derivative (with respect to the optimization variable) is known and computable. I use the default ...
1
vote
1answer
45 views

How to prove the demicountinuity of nonlinear operators?

Define a nonlinear operator $\mathbf{J}(\mathbf{x}):~\mathbb{R}^3 \rightarrow \mathbb{R}^3$ as $$ \mathbf{J}(\mathbf{x}):= |\mathbf{x}|^{-\alpha}\mathbf{x},~0<\alpha<1. $$ How to prove that ...
2
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2answers
233 views

Are solutions to optimization problems with smooth, continuous, and strictly concave objective functions and linear constraints always unique?

As an example, if I have a minimzation problem where my objective function is represented by a sphere in n dimensions (one dimension per decision variable), and all my constraints are linear, then ...
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2answers
61 views

$f(x_1,x_2)=\frac{x_1^2}{x_2}$ quasiconvex and/or quasiconcave or nothing on $\mathcal R\times \mathcal R$?

Related to the 3.16e question in Boyd's book. It asks what is $f$ in $\mathcal R\times R_{++}$. I am not interested in it but related thing when the domain is larger. So $f(x_1,x_2)=\frac{x_1^2}{x_2}$ ...
1
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1answer
83 views

First-order necessary condition for relative minimum point

I'm studying linear and nonlinear programming and I came across with the following proposition : given $\rm x\in\Omega$ we are motivated to say that a vector $\mathbf d$ is a feasible direction at ...
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2answers
23 views

Show that $x_1^2+x_2^2+(x_1-x_2)^3 \rightarrow \min$ has no solution

How can I show (preferably using the Bolzano-Weierstrass theorem), that $x_1^2+x_2^2+(x_1-x_2)^3 \rightarrow \min$ has no solution? I can see that it is true, but how can I show it?
1
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1answer
42 views

A non-linear optimization problem

I have the following optimization problem on the variables $a_1, ..., a_n$: $$ minimize \frac{\sum_{k=1}^{n}\max(k\cdot a_{k},1)}{\sum_{k=1}^{n}a_{k}} $$ $$ such\ that\ \ 0\leq a_k\leq 1\ \ \ (k=1, ...
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0answers
70 views

Levenberg-Marquardt, QR decomposition

Could anybody explain, how the Levenberg-Marquardt method may be solved using the QR decomposition? I know a current solution ...
1
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0answers
260 views

How to solve nonlinear constrained optimization in Matlab?

I have to solve a nonlinear constrained function in matlab, and I am not familiar with it's commands. the problem is: minimize $E(b,c)$ constraints: $k1< c\sqrt{b}< k2 ; c/6>k3$ Note: E(b,c) ...
2
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1answer
151 views

Prove or disprove the conjecture about the function below.

After thousands of numerical tests we stated the conjecture that their is exactly one local extremum of the function below. $$ {\rm f}\left(w\right) = {1 \over 2}\sum_{i = 1}^{n}\left({1 \over 1 + ...
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5answers
130 views

How to find the minimum of the function?

How to find the minimum of the following function $$ {\rm f}\left(w\right) = {1 \over 2}\sum_{i = 1}^{n}\left({1 \over 1 + {\rm e}^{-x_{i}\,w}} -y_{i}\right)^{2} $$ where $x_{i}, y_{i} \in \left(0, ...
3
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0answers
24 views

How does this polar function behave?

I came across this question in my textbook for Nonlinear Optimisation and I don't know what to do: Consider the function: $$ f(x_1,x_2)=(r-1)^2-\frac{1}{2}(r-1)^2\cos \left( \frac{1}{r-1}-\phi ...
1
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1answer
277 views

Definition of tangent cone in continuous optimization .

Looking at the definition of tangent cone in continuous optimization : If $M$ is a open subset of $\mathbb R^n$ $x \in M$, The tangent cone of $M$ at $x$ is defined by $$\mathbb T (M, x) = \big\{d ...
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0answers
61 views

Some problems with a proof of the Farkas Lemma

The following is a proof of the Farkas Lemma that is creating me quite some problems. [I presented the all proof simply to point out the notation used by the author.] My problem is with the last part ...
1
vote
1answer
122 views

Minimizing a linear function on a strictly convex set.

All the theorems that I know considering the uniqueness of a solution to a minimization/maximization problem requires the strict convexity/strict concavity of the objective function. But consider the ...
0
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2answers
33 views

Maximum of convex functions

how can i proof that: If $f_1, . . . , f_m$ are convex functions,than function $F(x) = \max(f_1(x), \dots , f_m(x))$ is convex? thanx for help.
1
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1answer
99 views

Third and higher order optimality conditions?

In the derivation of first and second order optimality criteria for a vector $X^*$ to be a local optimum to an unconstrained problem, we ignore the higher order terms of Taylor's expansion as we ...
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0answers
63 views

How do I find out if a critical point of a function is a maximum or a minimum?

If I've found the critical point of a function defined in some constraint (perhaps using Lagrange multipliers and the like); how do I find out if it's a relative/global maximum/minimum of a function ...
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0answers
24 views

How to check if steepest gradient method will converge?

So I have this function $ f(x,y) = x^4 - 2x^2 +x + 4y^2 $ and I want to know if the steepest gradient method will converge if I pick an arbitrary point and apply said method. My initial thought ...
3
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3answers
61 views

Minimization of $log_{a}(bc)+log_{b}(ac)+log_{c}(ab)$?

I am trying to find the minimal value of the expression: $log_{a}(bc)+log_{b}(ac)+log_{c}(ab)$ I think experience gives that the variables should be equal, if so then the minimal value is 6, but ...
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0answers
50 views

Using Newton's method to find an optimized matrix

I'm trying to apply Newton's method to find a local optimum of the matrix $\Sigma$ to minimize the objective function: $f(\Sigma) = -\sum_{n=1}^{N}\left(-\ln{2\pi} - ...
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1answer
26 views

Help in Linear summation of n(any given number)

The original formula is this. We're computing the complexity of an insertion sort. How did the first formula turned into the second formula?
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1answer
47 views

Uniqueness of Solution to non linear polynomial equations given by lagranges method

When considering Lagrange's method of multipliers for finding maximal solutions to a set of non-linear equations, I have reached a set of 4 equations in 4 real unknowns, $(a,b,c,\lambda)$: ...
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0answers
34 views

Decomposition of a symmetric semi-definite matrix into sums of sparse symmetric semi-definite matrix

I'll first provide the background. Let $x\in\mathbb{R}^N$ be decomposed into $n$ non-overlapping blocks of variables $x^{(1)},\ldots,x^{(n)}$. We say that $f:\mathbb{R}^N\rightarrow\mathbb{R}$ is ...
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0answers
55 views

Fitting a sine using linear regression

If I have two functions $s_1 = A_1 \sin(\theta+\phi)$ and $s_2 = A_2 \cos(\theta+\phi)$ is it possible to fit a sine or a cosine using linear regression? I usually have much less that a period ...
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0answers
28 views

Nonlinear optimisation of Expectation

I am preparing for my exams and I can't get my head around the following question. I know there exists a general method for solving these problems but I don't know where to start. I would greatly ...
2
votes
2answers
61 views

$\sum\limits_{k=0}^{19} \sqrt{1+u_k^2} \rightarrow \min$

Solve $\sum\limits_{k=0}^{19} \sqrt{1+u_k^2} \rightarrow \min$, such that $x_0 = 0, x_{20} = 5$ and $x_{k+1} - x_k = u_k$. I think I know how to solve problems like these recursively, but I ...