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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3
votes
1answer
33 views

What's the terminology for this alternative minimization algorithm?

Say the model is $F(x_1)G(x_2)Z(x_3) = y \in \mathbb{R}^N$, with $F,G,Z$ explicitly known, we are given observation of $y$ as $y_b \in \mathbb{R}^N$ to find the value of $x_1$, $x_2$, $x_3$ for each ...
4
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0answers
49 views

Sensitivity of BFGS to the accuracy of the gradient

I am studying how to speed-up the BFGS method using quantum computing techniques. I have used a method of speeding up the gradient of the function, but it sacrifices the precision value of the ...
2
votes
2answers
37 views

How to include penalty in a Objective Function with Python? GEKKO

I'm trying to include a "great M" penalty in my objective function. I want use the entry x vector values as entry values in a function. A fixed maximum value is took initially for the returned value ...
3
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2answers
54 views

MINLP with GEKKO - Modeling discrete variables

I'm trying to define a MINLP optimization problem with GEKKO in Python, and I want to use some variables with fixed values. For my first variable, x1, I need to define the following values (as would ...
3
votes
1answer
48 views

Optimizing for multiple objectives

Optimizing two models here, each model having its own set of parameters and an objective, but both models run on the same data which is difficult to compute, and which is computed based on both models'...
2
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0answers
39 views

Classification of multiobjective optimization algorithms

I am looking for a good (canonical?) overview paper(s)/book(s) on the classification of multiobjective optimization algorithms. I am focused on obtaining a representative set of Pareto optimal ...
4
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0answers
76 views

An optimization method for bounding the eigenvalues of a unknown non symmetric matrix

Given a positive objective function $f$ that acts on a real-valued matrix $A$, I am interested in the following problem $$\underset{A \in \mathbb{R}^{n \times n}}{\text{minimize}} \quad f(A) \quad \...
3
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0answers
103 views

A maximization problem, with motivation in machine learning

Consider the minimization problem described this paper. Let $f_{\lambda}$ be the minimizer. As a part of extending my work, I am able to show the following facts $$\lim_\limits{\lambda \to 0}\|f_{\...
2
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1answer
70 views

What is this discrete optimization problem called?

It feels like this problem should be commonplace, but I don't know what it's called: Minimize $$ \sum_{i=1}^{n}a^{(i)}_{k_i} + \sum_{i=1}^n\sum_{j=i+1}^n b^{(ij)}_{k_i k_j} $$ with respect to ...
1
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0answers
9 views

Long AMPL model preparation time

We deal with a large-scale linear optimization problem (~50000 variables and ~4000000 constraints). We use AMPL Studio modeling environment for problem modeling and then calling linear solver (CPLEX, ...
5
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1answer
44 views

Term for an small optimisation algorithm used as a subroutine

Is there a term describing a specialised solver which is used as a subroutine or a different, larger solver? For example, a gradient descent solver which, at each step, uses a line search to optimise ...
1
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0answers
58 views

How can I solve the matrix optimization problem where denominator and numerator are different?

I want to solve the following maximization problem in $\mathbf{X}\in {\mathbb{R}}^{{m} \times {n}}$ \begin{eqnarray} \begin{split} \quad\max_\mathbf{X} \frac{\mathbf{Tr}(\mathbf{X}^\top \mathbf{Q} \...
1
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0answers
37 views

least squared optimization

I want to decompose a list of 3D vectors $X_j$ as linear combination of five 3D verctors $C_k$ $$X_j= \sum_{i=1}^{5}{w_{ji}C_i}$$ both $X_j$ and $C_i$ are 3 components vectors $$C= \begin{bmatrix} ...
1
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0answers
71 views

How to perform local sensitivity analysis for partial differential equations

I am looking for a way to do local sensitivity analysis for PDEs, preferably in Python. I get the impression that discretizing the equation then treating it as an ODE could work; however, would that ...
2
votes
1answer
116 views

Simultaneously maximize and minimize

I am virtually new to optimization (saw it years ago in a very shallow course) and now I came across a problem that I believe would require from it. The problem is I don't know exactly how to proceed. ...
1
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0answers
47 views

Kinetic preconditioning

Publication arXiv:0804.2583 describes a method for doing self-consistent iteration without having to diagonalize the Hamiltonian operator at every step. IX. PRECONDITIONING As already ...
0
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0answers
44 views

Need an example Legendre-Gauss-Radau pseudospectral differentiation matrix or Matlab code

I'm trying to implement various kinds of pseudospectral methods for direct optimization in Matlab using IPOPT. I've got some working Legendre-Gauss-Lobatto code, but would like to use the flipped ...
3
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1answer
73 views

Geometric Programming - symbolic version

I am interested in finding minimizers of functionals of the type $\sum x^ay^bz^c$ where the exponents are 1, 0 or -1. I have codes to find such minimizers when they exist up to machine precision, ...
1
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0answers
58 views

How to use Wolfe-Powell step-size control in quasi-Newton method?

I'm trying to find the minimum of a function using the quasi-Newton method with the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. But I want to change the following implementation, so that: 1) ...
3
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0answers
43 views

Constraint solver vs Bayesian optimizer for fast discontinuous processes

I have a complex domain-specific process that accepts inputs: 10-500 inputs, where each input is of type: enum: choice between multiple string or numeric values int: integers float: floating point ...
1
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0answers
66 views

Best optimizer for unconnstrained non-convex nonlinear least-square optimization problem?

I am looking for a very good optimizer to the following problem: $$\min_{P,\Theta}\lVert APD(\Theta)P^{-1} -B \rVert_F$$ where $A,B \in \mathbb{R}^{n\times m}$, $P \in \mathbb{R}^{m\times m}$, $D\in \...
1
vote
1answer
60 views

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 (...
1
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0answers
43 views

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 ...
5
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0answers
94 views

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....
4
votes
1answer
36 views

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 ...
4
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0answers
60 views

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 ...
2
votes
1answer
66 views

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 ...
3
votes
1answer
88 views

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 ...
2
votes
1answer
75 views

How to compute the determinant of Hessian of a multivariable function?

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 ...
3
votes
2answers
67 views

Convexity of Sum of $k$-smallest Eigenvalue

If I have a real positive definite matrix $A\in\mathbb{R}^{n\times n}$, and denote its eigenvalues as $\lambda_1\leq \lambda_2 \leq ... \leq \lambda_n $. Define the function as $f(A)=\sum_{i=1}^{k} \...
5
votes
2answers
109 views

Choose a subset of $m$ columns that maximize $|A^T A|$?

I have a set of $n$-dimensional vectors, and would like to choose $m$ of them to become the columns of an $n\times m$ matrix. I would like to choose the subset that maximizes $|A^T A|$, where $A^T$ is ...
0
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0answers
33 views

Inverse kinematics BFGS divergence

I am trying to implement inverse kinematics solver using BFGS as stated in the paper Xia2017. In the test experiment, i created 4 objects in 3-dimensional space: Node, Node1, Node2, Node3. Each Node ...
0
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0answers
31 views

Parameter estimation using fmincon

This is a follow up to my previous question posted here. I am solving an optimization problem using fmincon in MATLAB. There are no equality constraints in my model....
0
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0answers
43 views

Parameter estimation using shooting method

I want to do the following, I have a set of 20 first order differential equations and I want to estimate some of the parameters. I've got the following initial and boundary conditions. The initial ...
3
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0answers
63 views

Solve ODE with non-negative and maximization constraints

My task is to solve $$\eta_k\frac{d^2C_k}{dz}(z)=-e_k, k = 1,2,3$$ $$C_k\ge0$$ $$C_1(0)=0, C_2(0)=A, C_3(0)=0$$ $$C_1(L)=B, \frac{dC_2}{dz}(L)=0, \frac{dC_3}{dz}(L)=0$$ with $$e_1 = -\beta_1-\beta_3$...
1
vote
1answer
79 views

Is there a name for this integer linear optimization problem?

I have an integer linear programming problem of the form: $$\DeclareMathOperator{\tr}{tr} \min \tr WX$$ subject to: $$\begin{align} \sum_j X_{ij} < c_i && \forall i \\ \sum_i X_{ij} = 1 &...
1
vote
1answer
134 views

How do I solve the matrix equality constrained optimization problem using Lagrangian multipliers?

Solve the following minimization problem in $\mathbf{X} \in \mathbb{R}^{m \times n}$ $$\begin{array}{ll} \text{minimize} & \frac 12 \| \mathbf{X}\mathbf{X}^T -\mathbf{A} \|^2_\mathcal{F}\\ \text{...
2
votes
1answer
91 views

Formulation of the least-squares parameter estimation problem

I have a system of 10 ordinary differential equations of the form, $$\frac{dy_1}{dt} = f1(V1,k1,y1,y2)\\ \vdots \\ \frac{dy_{10}}{dt} = f_{10}(V_{10},k_{10},y_{9},y_{10}) $$ I want to estimate the ...
0
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0answers
38 views

Scipy basinhopping custom step update and constrained looping

I am searching for the global minimum of a certain function and trying to use its gradient (here same as Jacobin) to guide the step counter. However, my x is fix ...
0
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0answers
13 views

Finding Maximum Value of CST Parameterization over an interval

I have a CST parameterization for a shape over an interval (0,1), so I have y as a function of x like so $$y = C(x)*s(x)$$ where $$C(x) = x^{n1}*(1-x)^{n2}$$ and $$S(x) = \sum_{i = 0}^{n} A_i(x)^i(1-x)...
0
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0answers
22 views

convex atomic function reformulation to meet concave dcp rule requirements

I have an atomic constraint of the form abs(w - w_prev) >= some_threshold It is supposed to get every value equal to or above my threshold. I am working on a ...
2
votes
0answers
38 views

Biconvex problem whose objective function depends on only one variable

I am solving the following biconvex problem: $$\min_{x,y} f(y)$$ $$s.t. ~~ g(x) \leq 0$$ $$~~~~~h(x,y) = 0$$ $$x \in X, y \in Y$$ where $X$ and $Y$ are compact convex sets, $g(x)$ and $f(y)$ are ...
4
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1answer
86 views

Examples of problems that cannot be formulated as optimization problems

An optimization problem has 3 main components: decision variables, constraints and an objective function. Such a problem can be mathematically modelled and solved using an optimization solver. For ...
0
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1answer
64 views

Solve multi-dimensional optimization problem using basinhopping

I am searching for an optimization solution, which is a 8d vector representing 4 complex elements, where each element is within the complex circle with maximal radius 1.2. The objective function is: ...
3
votes
2answers
94 views

Optimization techniques for expensive multi-variable functions

I'm working with a finite element model in which I'm interested to minimize the average temperature at a surface. I have 15 independent variables in my model, including geometry, materials, flows, ...
2
votes
3answers
136 views

Find a solution of large system of inequalities

I have a large system of homogenous inequalities involving 33 real unknowns of the form $$ \vec{F}(z_i)^T \cdot \vec{X}>0\, $$ where $\vec{X} = \left(x_1,...,x_{24}\right)^T$ are the unknowns and ...
3
votes
1answer
60 views

Non-parametric models as solutions to Partial Differential Equations

In the realm of scientific computing, there are a plethora of techniques developed to solve Partial Differential Equations (PDEs). Many of the popular methods are variants of common techniques such as ...
5
votes
1answer
68 views

What is the name for this type of constraint?

I have what would be a straightforward mixed-integer linear programming problem, except for the fact that some of the constraints are of the form $f(x_1,x_2,x_3,\ldots,x_n) < c$, where $f$ is 'take ...
0
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0answers
13 views

Cost functions to judge time/memory/accuracy tradeoffs

I am working on an interesting algorithm: Its absolute error is exponential in a parameter $j \in \mathbb{N}$, and for a given $j$, I have complete freedom to choose between an $\mathcal{O}(1)$ time-...
0
votes
1answer
18 views

Minimize squared error of linear function

Let $M$ be a $m \times n$ matrix, $x$ a $n$-vector, $y$ a $m$-vector, and $\|\cdot\|_2$ represent the $L_2$ norm (i.e., Euclidean norm). Given $M,y$, the goal is to find $x$ that minimizes the ...