Optimization Definition and 629 Threads

TL;DR Summary: Applied mechanics, mechanics, optimization, dynamics, kinematics Hi, I'm trying to finish this assignment and I'm not completely sure how to proceed. Should I first create the constraint equations, then the kinematics to get the derivatives for velocities and accelerations...

I have a problem that I imagine does not have a closed-form solution and requires the use of some kind of optimization solver. I am not an engineer myself, so forgive me if the question seems stupid. The problem is as follows: I have a circle bound in a square, and an arm going from the center...

Hello, I need help please. I have the following optimization problem defined as \begin{equation} \begin{aligned} & (\mathbf{P1}) \quad \max_{\mathbf{z}} \quad \left| d -\sum_{n=1}^{N} \frac{c_n}{f_n + z_n} \right|^2 \\ & \text{subject to} \quad \sum_{n=1}^{N} \frac{|a_n|^2 \text{Re}(z_n)}{|f_n...

Hello! I have a matrix (about 20 x 20), which corresponds to a given Hamiltonian. I would like to write an optimization code that matches the eigenvalues of this matrix to some experimentally measured energies. I wanted to use gradient descent, but that seems to not work in a straightforward...

I have a matrix of dimension 56*56, each row and column represent the compatibility of one person with the rest of the people. A sample matrix could be Alejandro Ana Beatriz Jose Juan Luz Maria Ruben...

Hello, I'm facing a practical optimization problem for which I don't know whether a standard approach exists or not. I would have liked to rephrase the problem in a more general way, for the sake of "good math", but I'm afraid I would leave out some details that might be relevant. So, I'm going...

I was checking bait cannons and potato guns on the internet because they are fun. Maybe one day I'll build my own. First of all, these cannons use multiple sources of energy (combustion using hair spray, dry ice, etc.). I'll just consider compressed air cannons because I think they are the most...

https://arstechnica.com/science/2023/06/googles-deepmind-develops-a-system-that-writes-efficient-algorithms/

This is basically a physics problem but I will try my best to highlight the mathematics behind it. Suppose I have two functions: $$T(z,B)=\frac{\text{z}^3 e^{-3 A(\text{z})-B^2 \text{z}^2}}{4 \pi \int_0^{\text{z}} \xi ^3 e^{-3 A(\xi )-B^2 \xi ^2} \, d\xi },$$ $$\phi(z,B)=\int_0^z...

I have a likelihood function that has one global minima, but a lot of local ones too. I attach a figure with the likelihood function in 2D (it has two parameters). I have added a 3D view and a surface view of the likelihood function. I know there are many global optimizers that can be used to...

Hey, gotta do some explanation first: I assume you know how roulette works. (if you dont: ball is thrown into a pit and it can either land on red, black or zero, each having a certain likeliness to land there. you can bet on where the ball will land) let's assume unrealistically you have the...

Mentor note: For LaTeX here at this site, don't use single $ characters -- they don't work at all. See our LaTeX tutorial from the link at the lower left corner of the input text pane. I have a function dependent on 4 variables ##f(r_1,r_2,q_1,q)##. I'm looking to minimize this function in the...

I'm reading the book Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, and currently reading this chapter on numerical methods--specifically, the section on constrained optimization. The book states the following. Suppose we wish to minimize a function...

We are given the problem min x3-x42 such that (1): x12 + x3 = 2 and (2): (x2-x4)(x2+x4)=1. What I did was solve for x3 in (1) and then solve for x4 in (2). I substituted those equations into min x3-x42 and I obtain the solution: 2-x12-x22+1, would this be the correct approach to this problem...

I know to solve this problem we need to see if x1sinx1 is convex and if the constraint is convex. I already know that x1sinx1 is not convex so the problem is not convex, but for proving that this function is not convex is where I am confused. But how do I go about showing this? I'm assuming I...

f(x)=ln(|x1|+1)+(-2x1 2 +3x2 2 + 2x3 3) + sin(x1 + x2 + x3), for this problem in particular would be it be sufficient to find the Hessian and to see if that matrix is semi positive definite to determine if it convex?

This is the code that i wrote Clear["Global`*"] Z = 500; W = 100000; G = 250; H = 100; K = 0.5; T = 30; L = 4000; P = 5; S = 2.5; Y = 1; A = 0.1; V = 2.5; J = 8000; f[x_] := 1/ x {(J*Z*x*(2*Y - x))/( 2*Y) - ((W + T*G) + ((L + T*P)*2*Z*Y*(1 - ((Y - x)/Y)^1.5))/ 3 + (H + T*S +...

Hello, I am using the Lagrange multipliers method to find the extremums of ##f(x,y)## subjected to the constraint ##g(x,y)##, an ellipse. So far, I have successfully identified several triplets ##(x^∗,y^∗,λ^∗)## such that each triplet is a stationary point for the Lagrangian: ##\nabla...

ABAQUS provides geometric restrictions such as a planer, rotational, and other symmetric, but there is no axis symmetric restriction. I know that the 2D axis symmetric element model could be possible to make in PART section. But I want to know that a full 3D element model could be optimized by...

Hi, I was reading through some notes on standard problems and their corresponding dual problems. I came across the L2 norm minimization for an equality constraint, and then I thought how one might formulate the dual problem if we had an L1-norm instead. Question: Consider the following...

Hi, I was working through the following problem and I am getting confused with the solution's definition of the dual. Problem: Given the optimization problem: minimize ## x^2 + 1 ## s.t. ## (x - 2) (x - 4) \leq 0 ## Attempt: I can define the Lagrangian as: L(x, \lambda) = (x^2 + 1) + \lambda...

Hello, I am better studying the theory that is the basis of Bayesian optimization with a Gaussian Process and the acquisition function EI. I would like to expose what I think I understand and ask you to correct me if I'm wrong. The aim is to find the best ##\theta## parameters for a parametric...

https://lh5.googleusercontent.com/aEaRfwwvnXOSUT8p390UKsIjrbVi2ERlBaKjwUDR3JoQOEw8bCLhQIek9wPo83GrJ8wqG7WTC1p1eQRgPdap9cPx9gt8zCQnibrb6BQjyvYVS91m2c79diOIVqHeKG0uSIo6phoT So I messed up in a tactical move. I was studying artificial intelligence for my backlog exam(exam that I failed also called...

So I messed up in a tactical move. I was studying artificial intelligence for my backlog exam(exam that I failed also called supplementary exam, re-exam, retaking exam). That was so huge and due to lots of other reasons (I don't want to sound whining so not mentioning them), I am here. I have...

Gradient descent is numerical optimization method for finding local/global minimum of function. It is given by following formula: $$ x_{n+1} = x_n - \alpha \nabla f(x_n) $$ There is countless content on internet about this method use in machine learning. However, there is one thing I don't...

Hi, I was working through the following optimization problem, and am getting stuck on how to get to the dual problem that is being presented. Question: Find the dual problem for the semidefinite primal problem below: min_{X} tr(C^T X) \text{subject to} AX = B X \succeq 0 (the answer is...

Hi, I am working on the following optimization problem, and am confused how to apply the Lagrangian in the following scenario: Question: Let us look at the following problem \min_{x \in \mathbb{R}_{+} ^{n}} \sum_{j=1}^{m} x_j log(x_j) \text{subject to} A \vec{x} \leq b \rightarrow A\vec{x}...

See attached screenshot. Stumped on this, I'll take anything at this point (hints, solution, etc).

Summary:: Hi, this is an exercise from an algorithm course. I have been trying for hours but I have no successful ideas on how to solve it. I can only understand that DP is the correct approach, since Greedy method does not work. Suppose you have *n* friends that wants to give you an amount of...

I tried using hamilton method but i don't think that's correct

Consider the following theorem: Theorem: Let ##f## be a concave differentiable function and let ##g## be a concave function. Then: ##y \in argmax_{x} {f(x)+g(x)}## if and only if ##y \in argmax_{x} {f(y)+f'(y)(x-y)+g(x)}.## The intuition is that local maxima and global maxima coincide for...

Hello There, I am studying docking of ligand molecules into DNA using Autodock Vina. Before doing that I optimize the ligand molecule using Gaussian 16. I want to know how can we get the PDB format after optimization. Do I just need to open the .chk file and save it as PDB format or do I need...

Hey! :giggle: Business operates on the basis of the production function $Q=25\cdot K^{1/3}\cdot L^{2/3}$ (where $L$ = units of work and $K$ = units of capital). If the prices of inputs $K$ and $L$ are respectively $3$ euros and $6$ euros per unit, then find : a) the optimal combination of...

Say for example I have a dataset (X, Y) which I need to fit to the function y = Ax^2 + By + Cxy. How do I retrieve values of A, B, and C such that they can only be integers? As of now I'm doing grid search which is so taxing.

I have a set of data (representing the strength distribution of samples), and I would like to fit a normal-Weibull grafted distribution. To the left of a specified graft point, the distribution is Weibull, and to the right it's normal. At the graft point, the value and the first derivative are...

Hi, I have an attempt at a plate heat exchanger (condenser) that uses water to condenser refrigerant, as a part of a heat pump. I have a total heat load of 12.01 kW. My current heat load is 10 kW. I have an analytical error on the wall temperature of about 23%, if I use Excel's Solver to...

Problem: Solution: My question: My reasoning was that if x is max at the point then the gradient vector of g at the point has only x component; that is ##g_y=0,\, g_z=0##. This way I got: $$\begin{cases} 4y^3+x+z=0\\ \\ 4z^3+x+y=0\\ \\ \underbrace{x^4+y^4+z^4+xy+yz+zx=6}_\text{constraint...

Please I do not want the answer, I just want understanding as to why my logic is faulty. Included as an attachment is how I picture the problem. My logic: Take the volume of the cone, subtract it by the volume of the cylinder. Take the derivative. from here I can find the point that the cone...

Allegedly Frechet derivatives are used in optimization problems in mechanics, but I have not found a clear example of this. Does anyone know of an example to go through? I would think because of the significance of Lagrangian mechanics that it could be more related to a variational calculus...

The following is the mathematical expression for my model's rate expression. Variables $x,y$ are the controlling parameter, while the rest are positive constants. $$\max_{x,y} \ ax + by^3 \ (s.t. \ 0\leq x \leq 1,\ 0\leq y\leq1)$$ Can I mathematically say that it is a convex problem within...

I am trying to troubleshoot why GFORTRAN versions beyond 5.4 will not compile with optimization on some of my .f source. You can request options included in each level by: Gfortran -Q -O1 --help=optimizers > listO1.txt (as an example) When I enter the enabled flags individually and compile...

Hi all, (Please move to general or mechanical engineering sub-forum if more appropriate over there. I put this here as it is essentially a mathematics problem.) Broken into sections: - problem categorization (what type of problem I think I have), - the question, - specifics (description of the...

Find the maximum and the minimum values of $S = (1 - x_1)(1 -y_1) + (1 - x_2)(1 - y_2)$ for real numbers $x_1, x_2, y_1,y_2$ with $x_1^2 + x_2^2 = y_1^2 + y_2^2 = 2013$.

I am writing a java application that would let me bulk send emails. The first problem I have is that of performance; approximately 15 seconds per 5 emails. The second problem, which is the more important, is that my JavaFX is not updating the scene. My code below shows that the way I intended...

\begin{equation} y_{1}{}'=y_1{}+y_{2} \end{equation} \begin{equation} y_{2}{}'=y_2{}+u \end{equation} build a control \begin{equation} u \epsilon L^{2} (0,1) \end{equation} for the care of the appropriate system solution \begin{equation} y_{1}(0)=y_{2}(0)=0 \end{equation} satisfy...

My Attempt :We need to maximize ## D=\sqrt{x^2+(y+2)^2} ## subject to the constraint ##4x^2 + 5y^2 = 20##. From the constraint equation, we can write ##x^2=\frac{20-5y^2}{4}## Using this in the formula for distance, ##D=\sqrt{\frac{20-5y^2}{4}+(y+2)^2}## Differentiating this wrt y, and...

attached resolution attempt

The Euler Lagrange equation finds functions ##x_i(t)## which optimizes the definite integral ##\int L(x_i(t),\dot x_i(t))dt## Is there any extensions of this to multiple integrals? How do we optimize ##\int \int \int L(x(t,u,v),\dot x(t,u,v))dtdudv## ? In particular I was curious to try to...

I have a simple question as a layman in the field: Is this worth reading, and even more, is it a contribution to possibly shorten the endless discussions in this subforum? https://www.nature.com/articles/s41598-019-56357-3.pdf

A thing doing its own thingy thing could compute faster than a computer can compute.