Questions tagged [constrained-optimization]

Questions about optimization problems subject to additional constraints.

65 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
6
votes
0answers
147 views

An invertible matrix that minimizes the norm of the product with a given matrix

Given a fat matrix $B \in \mathbb{C}^{n \times m}$ (where $m > n$) with full row rank, I would like to find (numerically) a full-rank matrix $A$ that minimizes the Frobenius norm of the product $A ...
5
votes
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....
5
votes
0answers
317 views

Optimization on the manifold of stochastic matrices

So I have an optimization problem of the form $$\text{maximize}\hspace{3mm}f(A):{\bf R}^{K\times K}\rightarrow{\bf R}$$ $$\text{subject to}\hspace{19mm}A^T{\bf 1}=\bf{1}$$ $$\hspace{33mm}A\geq 0$$ ...
4
votes
0answers
62 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 ...
4
votes
0answers
76 views

Solution of constrained system of ODEs

Can someone point me in a direction to solve this kind of integral constrained system of ODEs. \begin{align} &\int_0^{1/2}\dot{y}^2(t)=p\\ &2\lambda_1\ddot{y}(t)+\pi cos(\pi y(t))=0\\ &y(...
4
votes
0answers
50 views

Obtainting KKT for QSDP for the trace inequality constraint

I am working on developing my own solver(for implementation on hardware), based on IPM for following problem: \begin{equation} \begin{split} \min_{X} \; \frac{1}{2}&\|X\|_F^2 + trace(CX)\\ \text{...
4
votes
0answers
158 views

How to apply an integrated constrain condition in FEM?

I'm running some simulation using FEM. In my model I need to apply a constraint condition to the governing equation. My governing equation similar to the diffusion equation as below: $$\frac{\...
4
votes
0answers
447 views

Best way to add a positivity constraint to Newton's Method

So given an objective function $f({\bf x})$, I would like to include a positivity constraint when I perform the fixed point iteration: $${\bf x}^{(t+1)}={\bf x}^{(t)} - \text{H}_f^{-1}\nabla f({\bf x}^...
4
votes
0answers
153 views

Eigenvalue-style optimization with quadratic constraints

Suppose $A\in\mathbb{R}^{n\times n}$ is symmetric and positive definite and that we have several symmetric matrices $B_i\in\mathbb{R}^{n\times n}$ that are low-rank and indefinite. I need an ...
3
votes
0answers
27 views

How to set up and solve acceleration-limited trajectory optimization problems?

I've been trying to learn how to solve simple acceleration-limited trajectory planning problems. I'm working in C++ and I've been using the Eigen library to do linear systems solving. I'm doing the ...
3
votes
0answers
20 views

Sequence planning with 3 machines

together! First of all, I have to mention that because of my background as an Industrial Engineer, I have limited abilities in mathematics, but am disciplined enough to expand myself from ...
3
votes
0answers
48 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 ...
3
votes
0answers
70 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$...
3
votes
0answers
92 views

Minimize number of rectangles that cover all the points

I have a 2d distribution of moving points with known trajectories represented in a 640x480 image. Here is the initial state: I have to find the minimum number of rectangles with fixed dimensions (...
3
votes
0answers
199 views

Optimal Control using Dynamic Programming - Optimizing for Furthest Distance

So I have been investigating a problem to get a glider with control of its elevator to fly as far as possible from any given initial state. To keep this simple, we will view this in 2D space with the ...
3
votes
0answers
74 views

linear relaxation of an optimization problem

I'm reading an article lately, and there is one point which confuses me. So, we have the following constrained binary quadratic problem. min $x^{T}Qx$ with the constraints that $Ax≤b$ and $x\in {0,...
3
votes
0answers
102 views

Applications of algorithm for solving systems of equations with uncertainty

We have been developing algorithms for detecting "robust" zeros of multidimensional functions $f: X\to\Bbb R^n$ where $X$ is an $m$-dimensional domain in $\Bbb R^m$. More precisely, for a given $f$, ...
3
votes
0answers
159 views

Find constrained vectors maximizing angles between them - methods?

This is related to a question I had asked earlier, with the distinction that earlier I did not have a non-linear objective functional to minimize. The problem is reproduced below with added ...
3
votes
0answers
72 views

numerical solver for stochastic optimal control problems

can any one recommend numerical solver (c/c++ library preferred) for stochastic optimal control problems? For deterministic optimal control I found something like that: http://abs-5.me.washington.edu/...
3
votes
0answers
72 views

Why not use this simpler variant of Stepwise Regression?

In stepwise regression, you step predictor by predictor, each time selecting the one with the greatest correlation with the measurement, subtracting greedily to leave a residual with no correlation to ...
2
votes
0answers
40 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 ...
2
votes
0answers
52 views

How to find two points within defined region in this constrained optimization problem?

I am doing a project related to robotics where I am using fmincon function from matlab to minimize the distance between the points ...
2
votes
0answers
40 views

Sensitivity Lagrangian solution general case

I have asked this question already on maths and mathoverflow. Just a question about a literature reference. I am writing a paper for engineers. Usually for the Lagrange multiplier problem $$ \...
2
votes
0answers
269 views

Convergence of a very large non-linear least squares optimization

(note: I also posted this question on stackoverflow before finding this community here, which seems a better place for it) I'm trying to solve the following problem: I have a lot (~80000) surface ...
2
votes
0answers
61 views

How to model pedestrian flow through subway systems?

I'm a New Yorker and take the subways every day. I have a growing interest in understanding the distribution of paths people take on the subways to work every day. I.e. if there are $n$ subway ...
2
votes
0answers
94 views

A least square problem with a fixed mean constraint and a subspace constraint

Let $V_1,\ldots,V_n$ be $n$ vector subspaces of a Hilbert space, $y_i\in V_i$ for each $i$ and $\overline{x}$ be a fixed vector. I want to solve the optimization problem: \begin{equation*} \begin{...
2
votes
0answers
206 views

Using Line Search Method for Constrained Optimization

Suppose we have a $f(x)$ to be minimized (we only know that $f(x)$ is three-differentiable), and a feasible, convex set of $S$ such that all $x$ belong to $S$. Using line search method, how we can "...
2
votes
0answers
41 views

$(max(0, f(x)))^2$ or $(max(0, exp(f(x))))^2$ for soft constraints with Gauss-Newton

I need some kind of inequality constraint in my optimization problems (rude version of SVM for example or skeleton based mesh fitting). However hard constraints is not suitable for me because ...
2
votes
0answers
63 views

Convergence of KKT equations for discrete parameter estimation problems

Consider a discrete constrained optimization problem: $$ \mathbf{q}_*^h= \arg \min {\cal J}^h(\mathbf{x}^h[\mathbf{q}^h],\mathbf{q}^h) $$ subject to the (weak-form) constraint $$ F^h[\mathbf{x}^h(\...
2
votes
0answers
335 views

Solving constrained BVP, singular Jacobian

The boundary value problem is $$ \begin{cases} \dot{x}_i = \begin{cases} (0.5D^{-1}\psi)_i, \text{ if }(0.5D^{-1}\psi)_i \le 0 \\ 0 \text{, otherwise} \end{cases} \\ \dot{\psi} = 2\Sigma x \\ x(0) =...
2
votes
0answers
91 views

non convex, non linear optimization involving matrix differential equation solution

I'm trying to develop an inferential procedure for a multivariate dependent Markov process. Basically, the procedure could be considered as a non linear regression, with a known dependence structure ...
2
votes
0answers
117 views

Hessian eigenvalues in 4D-VAR data assimilation

I am using variational data assimilation (4D-VAR) to estimate emissions of anthropogenic greenhouse gases using a rather complex atmospheric transport model. Hence, the optimal solution to my problem ...
2
votes
0answers
48 views

Inverted value is not consistent with expectation

We have a group of observations $$y = f(x_1, x_2, x_3) \enspace .$$ We have also a forward model $y = f(x_1, x_2)$. The forward model does not include $x_3$ because $x_3$ might include dozens of ...
2
votes
0answers
64 views

Fortran solver for the Sparse LSE problem

I was wondering if there is a Fortran library that contains a solver for the Sparse LSE(linear equality-constrained least squares) problem $$ min_{x}\|Cx-d\|^2 \text{ subject to } Ax=b $$ where $A$ ...
2
votes
0answers
80 views

About Convex Geometry

A consistency notion in constraint programming: Let $P = (X, D, C)$ be a CSP. Given a set of variables $Y \subseteq X$ with $|Y| = k -1$, a locally consistent instantiation $I$ on $Y$ is $k$-...
2
votes
0answers
129 views

Inverse problem with a rank-1 update

I hope you can help me out with this. I have to find the solution x to an inverse system $$ x=A^{-1}b $$ This inverse problem is basically a least square problem with a rank-1 update. $$ x=[uv^{T}...
1
vote
0answers
63 views

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)...
1
vote
0answers
11 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, ...
1
vote
0answers
34 views

Minimizing a polynomial with millions of monomials

I need to minimize a single polynomial $P(x_1,x_2,...,x_n)$ with the constraint that for each $i$, $0\leq x_i \leq 1$. The number of variables in my practical problem is at most $50$. The degree is at ...
1
vote
0answers
34 views

Logging vs outputs in iterative optimisation

I'm coding an iterative algorithm of constrained continuous optimisation. An augmented Lagrangian algorithm (outer) calls a bound-constrained L-BFGS-B algorithm (inner), which calls a line search ...
1
vote
0answers
35 views

Efficient numerical optimization of an “almost separable” function

I have come across an optimization problem with the following objective function: $$f(x_0,y_0,z_0,x_1,y_1,z_1,...,x_N,y_N,z_N) = \sum_{i=0}^N f_i(x_i,y_i,z_i, \alpha(x_{i+1}-x_i) + \beta(y_{i+1}-y_i))...
1
vote
0answers
44 views

Space covering optimization

I have the following problem: In the space $E=\{1, 2, \dots, N_x\} \times \{1, 2, \dots, N_y\}$, I want to define $N_R$ rectangles $R_k=\{x_k^0, \dots, x_k^1\}\times\{y_k^0, \dots, y_k^1\}$ which ...
1
vote
0answers
84 views

Sequential Quadratic Programming for Quadratically Constrained Quadratic Programs

A standard Quadratically Constrained Quadratic Program (QCQP) is of the form: $$ \underset{x}{minimize} \frac{1}{2}x^TP_{0}x + q_{0}^{T}x $$ $$ subject \; to \quad \frac{1}{2}x^TP_{i}x + q_{i}^{...
1
vote
0answers
97 views

functional second derivative

I'm trying to build a numerical solution for a parameter estimation problem of reaction-diffusion equation, using the adjoint method. To summarize it, I'm trying to minimize the function $$ G=\frac{...
1
vote
0answers
74 views

Find a vector B that minimizes |W-A*B|

I want to find a candidate vector $B$ that $$\min|(W - A_i * B_i)|$$ $$ a_i > 0,\ A_i=\{a_0,...,a_i\},\ B_i=\{-1,0,1\}^i$$ For example, given $$W = 0.6,\quad A_4 = [0.1, 0.2, 0.4, 0.7] $$ one ...
1
vote
0answers
53 views

Obtaining the lagrangian multipliers in an optimization problem

Suppose we have this simple optimization problem \begin{align*} \underset{x\in V}{\text{min}} &~ f(x) \\ \text{s.t.}& ~x \leq \beta \end{align*} Using slack variables \begin{align*} ...
1
vote
0answers
68 views

What are the numerical properties to consider between Augmented Lagrangian and the Penalty Method?

I'm interested in (locally) minimizing a smooth nonconvex objective function: $$ f(\textbf{x}_1, \textbf{y}_1,\cdots, \textbf{x}_n, \textbf{y}_n)=\sum_{i=1}^ng(\textbf{x}_i, \textbf{y}_i) $$ Subject ...
1
vote
0answers
86 views

constrained quadratic binary problems and quantum adiabatic evolution

I'm going through an article with title "Solving constrained quadratic binary problems via quantum adiabatic evolution" (reference 1). And there are several points confusing me a lot. This article is ...
1
vote
0answers
77 views

How does this Constrained Minimization algorithm work?

I don't fully understand the subsection 3.2 Constrained minimization of this paper. In particular, I don't understand the first step "Register active set" and the definition of projection $P(x)$. ...
1
vote
0answers
519 views

Are linear programming algorithms faster than quadratic programming algorithms?

I have an objective function that I can write either in quadratic programming (QP) such as $$\sum_{i=1}^N \sum_{j=1}^N C_{ij}^2$$ or as an LP problem $$\sum_{i=1}^N \sum_{j=1}^N |C_{ij}|$$ which can ...