Optimization is the process of choosing the "best" value among possible values. They are often formulated as questions on the minimization/maximization of functions, with or without constraints.

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Dual cone of a L1 norm cone?

I am listening to convex optimization lectures and I hear that dual cone of a $L1$ norm cone is a $L-\infty$ norm cone. Can anybody please explain how? I understand that every point in the dual cone ...
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200 views

Extreme of $\cos(A)\cos(B)\cos(C)$ in a triangle without calculus.

If $A,B,C$ angles of a triangle, show extreme value of $$\cos(A)\cos(B)\cos(C)$$ I have tried using $A+B+C=\pi$, and applying all and any trig formulas, also AM-GM, but nothing helps. On this topic ...
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1answer
54 views

Does it pay to know what you know?

Let's play a game. I ask you question a yes/no question, and you answer. You don't answer with a yes or no though, you answer with a probability of it being yes ($P \in (0,1)$). For example, I might ...
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+50

When might some a variable leave the basis?

In the simplex algorithm in linear programming, what are conditions for a variable to leave a basis (not necessarily basis for the/an optimal solution)? I'm supposed to list as many sufficient and ...
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16 views

Variational Calculus with Discrete Objective

I'm trying to infer a smooth, non-negative function from some given data ($\vec{m},\vec{\alpha},\vec{\beta}$). That is, I want to solve (I think) $$ \mathop{\arg\!\min}_{g \in ...
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A Basic Question E-views

I ask a question about E-views. Is the P-value in the picture less than 0.05 or greater than 0.05? I'm confused because of the presence of the sign '<' in front of 0.10. Please help mee. Thank you. ...
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48 views

Maxima and minima of $f(x)=\binom{16-x}{2x-1}+\binom{20-3x}{4x-5}$.

Find the maximum and minimum value of the function $f(x)=\binom{16-x}{2x-1}+\binom{20-3x}{4x-5}.$ ATTEMPT:- By A.M.-G.M. inequality, $\frac{a+b}{2}\ge\sqrt{ab}$, $\quad$ for $a,b\gt 0$ with equality ...
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25 views

How to explain polynomial coefficients by minimezed Error function?

We wish to predict ${\bf{t}}$ from an observed $\bf{x}$.We shall fit the data using a polynomial function of the form$$y({\bf{x}},{\bf{w}})=w_0+w_1x+w_2x^2+...+w_Mx^M=\sum_{j=0}^{M}w_jx^j$$ where $M$ ...
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0answers
21 views

How to use CVXOPT to solve an semidefinite programming problem

I'm using Sage to solve a problem and would like to use cvxopt to solve a sdp problem. Specifically, I have a list of expressions of the form $$c + \sum_{i,j} a_{i,j} q_{i,j}$$ where each $c$ and all ...
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26 views

Smallest distance of a point to a surface

Let $P$ be a hyperplane of dimension $n-1$ in the space $\mathbf{R}^n$, given some integer $n\ge 3$ (let's call the first axes $x,y,z,\ldots$). Then, fix a point $A \in P$ and define the surface ...
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17 views

Maximizing $g(x)$ and monotone transformation $f(g(x)$ is the same?

I have encountered that in some cases maximization of a function had been substituted with a maximization of its monotone transformation. For example, finding the min or max of $f(x,y) = ((x-1)^2 + ...
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1answer
807 views

Maximization of sum of two functions

Is there any relationship similar to the following. Let $X$ be the maximum of functions $f_1(x)+f_2(x)$. Let $X_1$ be a maximum of $f_1(x)$ and let $X_2$ be a maximum of $f_2(x)$. Is there any ...
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17 views

$\max\{c^Tx:Ax\le b,x\ge 0\}=+\infty$ iif it exists $j\in\{1,…,n\}$ such that $\max \{x_j:Ax\le b, x\ge 0\}=+\infty$

Show a vector $\vec c$ exists such that $\max\{c^Tx:Ax\le b,x\ge 0\}=+\infty$ if and only if it exists $j\in\{1,...,n\}$ such that $\max \{x_j:Ax\le b, x\ge 0\}=+\infty$ I'm only asking for a ...
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10 views

Convert this problem with 2-norm cost to an SOCP?

I am solving a non-convex problem via sequential convex optimization. Here is a minimal example of my problem at iteration $i$: $$ \begin{align*} \min_{\Delta t,F_i}&\left( \Delta ...
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3answers
381 views

A primitive function of $ e^{x^{2}} $

I made some efforts to set a closed form of primitive function of $ e^{x^{2}} $ i find this function : $ f(x)=\frac{x}{2x^{2}-1}e^{x^{2}} $ where : $f'(x)=(\frac{x}{2x^{2}-1}e^{x^{2}})'$= ...
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2answers
23 views

Application of A.M. -G.M. inequality

Let x, y,z be positive numbers. The least value of $ \frac{x(1+y)+y(1+z)+z(1+x)}{(xyz)^{.5}}$ is a) $\frac{9}{2^{.5}}$ b) 6 c) $\frac{1}{6^{.5}}$ d.) None of the above I tried applying the A.M. ...
2
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1answer
13 views

Euler- Lagrange, Several functions of 1 variable Question

In this question here, by solving the E-L equations for y and z, you get that $y'' = z$ and $z'' = y$. Thus $y'''' = y$ and $z'''' = z$ However, this solution is $ Ae^x + Be^{-x} + C\sin x + ...
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22 views

How to efficiently create balanced KD-Trees from a static set of points

From Wikipedia, KD-Trees: Alternative algorithms for building a balanced k-d tree presort the data prior to building the tree. They then maintain the order of the presort during tree construction ...
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1answer
27 views

On Boyd et al.'s convergence analysis of ADMM: Why do we need the convexity assumption?

Please refer to Boyd et al.'s convergence analysis of ADMM (Chapter 3 and Appendix A). My question is: Why do we need $f$ and $g$ to be convex? I don't see the need of this assumption. If the ...
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1answer
54 views

Is this a proper alternative way for math model for TSP(Travelling Salesman Problem)?

I have never seen a model that uses indexing in any article.So I have decided to publish it to be sure. I think indexing model is more suitable for generalizing the model than the subtour elimination ...
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18 views

Minimizing convex functions without compatible gradients

I've been working on a minimization problem for a while, involving "simple" conditions, but haven't been able to figure it out. I've tried using Lagrange Multipliers and KKT, but the presence of ...
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2answers
588 views

Convex Optimization of quadratic function with inequality constraints

How would I solve the following problem? $$\min_{x\in\mathbb{R}^n} x^T A x$$ subject to the constraints $$x_i\geq 1,\,i=1,\dots,n,$$ where A is positive semidefinite and symmetric. Is it possible to ...
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1answer
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How to describe minimization of L1 norm error using linear programming?

Given a set of $n$ pair points $(x_1, y_1), ..., (x_n, y_n)$ in the plane, I need to find a line $ax + by = c$ that fits the points of the L1 norm error points as closely as possible. I need a linear ...
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5answers
91 views

if $\sum\limits_{i=1}^n{x_i} = 1$, how do you choose the $x_i$'s such that $\sum\limits_{i=1}^n{x_i^2}$ is minimized?

if $\sum\limits_{i=1}^n{x_i} = 1$, how do you choose the $x_i$'s such that $\sum\limits_{i=1}^n{x_i^2}$ is minimized. I have an intuition that each $x_i = \frac{1}{n}$, but I don't know how to prove ...
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1answer
31 views

Converting generic linear problems into their dual

I'm revising how to do dual problems in linear algebra. I'm very weak in Linear programing but I struggle to cope with the topic during lectures and assignements. I have to convert the following ...
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2answers
689 views

Shortest distance between parallel line and plane

I've been doing questions regarding the shortest distance between lines/planes and points , and I've come across a question asking to find the shortest distance between a line and a plane which are ...
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14 views

Maximum Likelihood Estimation of a log function with sevaral parameters

I am trying to find out the parameters for which the function will be maximized !$$ \log L(\alpha,\beta,v) = v/\beta(e^{-\beta T} -1) + \alpha/\beta \sum_{i=1}^{n}(e^{-\beta(T-t_i)} -1) + ...
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1answer
26 views

Solving constrained Euler-Lagrange equations with Lagrange Multipliers (Geodesics)

I'm trying to solve a calculus of variations geodesics problem using Lagrange Multipliers, showing that the geodesics of a sphere are the so-called great circles. I am using a constrained Lagrangian ...
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1answer
776 views

Implementation of EM algorithm for Gaussian Mixture Models using Matlab

Using the EM algorithm, I want to train a Gaussian Mixture model using four components on a given dataset. The set is three dimensional and contains 300 samples. The problem is that after about 6 ...
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2answers
68 views

Finding the maximum area of a triangle with a perimeter constrain

Using graphical methods, determine the dimensions of a right triangle that has the largest possible area, given that the perimeter cannot be larger than $P$. The final answer should be in terms of ...
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Calculate stationary points of $x^3 \textrm e ^{\frac {-x^2} {a^2}}$ [closed]

Calculate all of the stationary points of $$x^3 \textrm e ^{\frac {-x^2} {a^2}}$$ where $a > 0$. Thanks in advance.
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34 views

Intuition about the Cauchy-Schwarz inequality and optimization problems

I'm trying to develop intuition about the Cauchy-Schwarz inequality. Suppose I have positive real vectors x and y. The values of x are already determined and I want to find the values of y that ...
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16 views

Does it make sense to compare sets (polygons) with different dimensions?

In the context of integer programming, I am considering 3 different linear models for a given problem. The goal is to determine which formulation is the tightest, that is, the one that gives the least ...
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213 views

Verification for maximum principle

Given optimal control problem $$ \dot x = f(t,x(t),u(t)), \quad x(0) = x_0,\\ J(u) = \int_0^T f^0(t,x(t),u(t))dt \to \min, $$ we can apply Pontryagin's maximum principle to get a necessary condition ...
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$\{x\in R^n | Ax \leq b\} \cap \{x \in R^n | Dx \leq d\}= \emptyset$ iff there is a vector $c \in R^n$ such that $c^Tx < c^T y$

Consider two non-empty polyhedra $P := \{x\in R^n | Ax \leq b\}$ and $Q := \{x \in R^n | Dx \leq d\}$. Show that $P \cap Q = \emptyset$ if and only if there is a vector $c \in R^n$ such that $c^Tx ...
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166 views

Prove an artificial variable that leaves the basis will never return.

This is in the context of the Big M Method in the simplex algorithm in linear programming. Prove an artificial variable that leaves the basis will never return. I have no idea how to start this. ...
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0answers
45 views

What values make the solutions in the optimal? infeasible? degenerate? etc

Note that $c_i$'s in the $z_j-c_j$ row are not coefficients of the $x_i$'s. We can use instead $r_1, r_2, r_3$ (r for row). I'm assuming there's a non-negativity constraint. we need to state ...
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45 views

Develop a model for determining the optimal production schedule in a manufacturing facility

I have to formulate (linearly) the following problem mathematically: What I tried: 1. Variables Let $x_{ijk} = 1$ if, in month k, product i should be made in production line j, where ...
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20 views

If the primal is unbounded, then the dual is infeasible.

In the context of duality in linear programming, prove that If the primal is unbounded, then the dual is infeasible. What I tried: The short version is that unbounded primal means a column ...
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Transforming sigmoid function to concave function [closed]

Can someone please tell me of a function that transforms a sigmoid function into a pure concave function?
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Derivative one-to-one around local minimum? [closed]

Let $f(x): \mathbb{X}\subset\mathbb{R}^{k}\rightarrow \mathbb{R}$. $f(x)$ is twice continuously differentiable on $\mathbb{X}$. Suppose $f(x)$ has a strict local minimum at $x=x^{*}$. Is it true that ...
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2answers
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Optimization of the surface area of a open rectangular box to find the cost of materials

A rectangular storage container with an open top is to have a volume of 10 cubic meters. The length of the box is twice its width. Material for the base costs ten dollars per square meter and for the ...
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0answers
14 views

Approximating a quadratic term in the constraint set as 2nd order Taylor expansion

I have an optimization problem in the following form: $$\min_{x,y} f(x)+g(y)$$ $$s.t.$$ $$Ax+h(y)=0$$ where $h(y)$ is a quadratic in $y$. Instead of solving this problem directly, $h(y)$ is ...
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1answer
75 views

How to construct a polynomial with minimum deviation from zero on the complex region?

I need to compute the analog of Chebyshev polynomials (which give the minimum deviation from zero on [-1,1]) on the given region $\Omega\subset \mathbb C$. More precisely: find $P_n$ such that ...
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Problem about find the extreme of a function (Multipliers of Lagrange)

Good morning, i have a problem with this: Find the maximum and minimum distances from the origin to the curve $g\left(x,y\right)=5x^{2}+6xy+5y^{2}$ I make this: Function to optimize: ...
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3answers
598 views

How to prove Lagrange multiplier theorem in a rigorous but intuitive way?

Following some text books, the Lagrange multiplier theorem can be described as follows. Let $U \subset \mathbb{R}^n$ be an open set and let $f:U\rightarrow \mathbb{R}, g:U\rightarrow \mathbb{R}$ be ...
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1answer
54 views

Solving a linear program thanks to complementary slackness theorem

Using the complementary slackness theorem, say if the following basis optimal: $$x_1*=0=x_5*,x_2*=4/3,x_3*=2/3,x_4*=5/3$$ \begin{cases} \max & 7x_1 ...
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0answers
19 views

Can a linear program be optimal if its basis is infeasible?

I want to know thanks to the dual theorem wether the following basis is or isn't optimal. That is to say looking for the slack variables. As far as the third line doesn't respect the constraints: ...
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11 views

Which coefficient to start with in the dictionary method?

I used to start with the variable with the biggest coefficient in the goal function (in the case of max). yet I read an article that behaving like this may lead to loop. It is rather preferred to do ...