# Questions tagged [optimization]

This tag is intended for questions on methods for the (constrained or unconstrained) minimization or maximization of functions.

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### Prove that the set of maximizers are independent of parameter in the objective function

A maximization problem reads as $$J(y) = \sum_{k=1}^{K} \sigma_k(y)^q \mathop{\rightarrow}^{y} max$$ where $q \in [1,\infty]$ is a user-defined parameter and functions $\sigma_k, k=\{1,\dots,K\}$ ...
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### Methods to approximate obective function gradients from point cloud

Problem statement: Assume that I have an objective function $f(x)$ which takes as input a $D$-dimensional vector $x\in\mathbb{R}^D$, and that $f(x)$ is sufficiently smooth. Assume further that I ...
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### How to approach geographic data interpolation by distance?

let's say I have a set of geographic locations (lat, lng) resulting from a query. Those locations have some kind of internal ranking, my set is sorted by this number in a descending order. Now I'm ...
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### How to obtain only the value of my variable using scipy.optimize.minimize

when I minimize a function using scipy.optimize.minimize I get a big list of things as a result, but I would like to only get the value of my variable, this is my code : ...
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### Multilevel minimization - boundary conditions

I am interested in minimizing $$min_{x \in R^{n^l}} f^l(x),$$ where $f^l(x)$ is nonlinear objective function arising from discretization of PDE. I would like to use nonlinear multilevel minimization ...
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### How to check the feasibility of a set of linear inequality constraint?

(The image of the whole problem is also included) Consider a set of linear inequalities constraint as: Ax >= b, 0 <= x <= L, where A(N,N), x(N,1), and b(N,1). It is assumed that the ...
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### Calculate Transformation Matrix between two sensors

My question is if I can calculate the transformation matrix between two sensors. Each sensor provides a $4\times 4$ matrix for every timestep recorded. The sensors are moving and have some noise in ...
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### Optimal line such that maximum points are between an upper and lower boundary

I have some 2D data and would like to find a line $y = mx + b$ such that a maximum number of points from the data is captured within the area between $y = mx + b + margin$ and $y = mx + b - margin$. ...
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### How to solve calculus of variations problems numerically?

For example, how to solve the well-known isoperimetric problem (i.e., to enclose the largest area with a fixed-length curve)? We can simplify things a bit and fix the two ends of the curve at $[a,0]$,...
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### Method for implementing QP solver with matrix terms?

I am trying to implement (in code) a QP solver for the following equation: $$\min_{u} u^{T} Wu$$ $$s.t. \; \beta u = \tau_{ref}$$ $$Au \leq b$$ See this document, section 5.1 (Page 35) $u$ is a ...
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### Ramp least squares estimation

With some given $s$ value, let \begin{equation} \begin{aligned} h(\beta)&=\min(\sum_{i=1}^n(Y_i - X_i\beta)^2, s)\\ &=\sum_{i=1}^n(Y_i - X_i\beta)^2-\max(0, \sum_{i=1}^n(Y_i - X_i\beta)...
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### Python-accessible industry-standard for unconstrained minimization that converges to machine precision?

I have an unconstrained minimization problem of many variables for which I know the gradient exactly. I turned to the conjugate gradient method contained in ...
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### Pivoted Cholesky vs Modified Cholesky

I am solving nonlinear least squares problems with the normal equations approach, so on each iteration, I need to solve: $$J^T J \delta = -J^T f$$ for the step $\delta$, where $J$ is a large (...
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### Finite dimensional optimization problem over dynamical system

I am interested in solving numerically the following mathematical problem Consider an ode of the form $$\dot q(t) = f(q(t),t_1,\ldots, t_N),\qquad t\in [0,T],$$ where $q\in \mathbb{R}^n$ is the ...
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### How to solve a 4th order nonnegative LASSO problem?

I need to solve the following 4th order nonnegative LASSO problem: $$\min_{x \geq 0} \quad || |Ax|^2 - b ||^2 + \lambda ||x||_1$$ where $|\cdot|^2$ denotes element-wise squared. $A$ is small size (e....
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### Single-variable multimodal derivative-free optimization (for a well-behaved function)

Are there well-established approaches to single-variable multimodal optimization? Given $f:\mathbb{R}\rightarrow\mathbb{R}$ that: has several local minima within a given range of interest $[a,b]$ is ...
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### Fast approximate solver for vehicle routing problem

I need to solve capacitated asymmetrical vehicle routing problem with time windows on ~30k points. Time limits for calculations are 2 hours. I've tried using Clarke and Wright savings algorithm, it is ...
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### User friendly scipy optimize wrapper package?

I'm creating too much throw away code for interfacing with the scipy optimize package in a user friendly way. (See code below for example of interruptible optimization that keeps last optimization ...
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### Why would BFGS converge to a local minima of a non-convex function but maintain a large gradient?

I'm using BFGS to optimize a smooth but non-convex function $f$ that is computed by a simulation. The simulation also gives me a semi-analytical gradient $g$, which is verified by the numerical ...
I have a function $F(\vec x)$ of many variables (let's say in the order of hundreds of thousands). I need to compute the determinant of the Hessian matrix at the point $x_0$. Is there a way to ...