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Related Code
Unconstrained Optimization Nonlinear
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Code 1-20 of 20   

Deterministic unconstrained optimization method using Powell.

This package has solvers for constrained and unconstrained L1 minimization, which is useful for compressed sensing.

u = COORDL1BREG(A,f,lambda) solves the minimization problem
min_u ||u||_1 subject to A*u = f
where A is an...

Demo graphical user interface that finds an unconstrained mean-variance efficient frontier given asset price data. This data can come from Yahoo finance, where you can find the optimial portfolio for any set of assets you choose, or from a...

This function can find the maximum of constrained and unconstrained problems with using of genetic algorithm (real coding). Also the performance of GA is plotted vs. the number of generations (for 2D problems).

It's a deterministic iterative zero order algorithm that can be used to solve unconstrained optimization problem. It finds the relative minimum of a two variables function with a deterministic iterative zero order algorithm.


The Kalman filter is actually a feedback approach to minimize the estimation error in terms of sum of square. This approach can be applied to general nonlinear optimization. This function shows a way using the extended Kalman filter to solve some...

This is a fully three-dimensional rigid body simulation engine. The bodies are unconstrained. This example demonstrates the simulation of a triple pendulum: three prismatic bars connected by springs bounce and swing freely.

SIMPGRIDSEARCH Multi-dimensional unconstrained nonlinear minimization using grid search + Simplex method.

X = SIMPGDSEARCH(OBJFUN,GDVALUES) returns a vector X that is a minimizer of the function described in OBJFUN (usually an m file:...

function [C,d]=eliminateConstraints(A,b) eliminates variables from a problem with linear equality constraints to give an unconstrained problem. This is useful e.g. when solving a problem with linear constraints and a nonlinear objective or further...

Constrained and Unconstrained, Analysis and Synthesis Prior Solvers for Jointly sparse Multiple Measurement Vectors.
Sparco is required for running the Matlab files. Download it from ans install it in...

Golden Section search for minimizing a nonlinear function in one dimension
Davidon-Fletcher-Powell (DFP) method. This is a method to solve an unconstrained nonlinear program

Fminsearch does not admit bound constraints.
However simple transformation methods exist to
convert a bound constrained problem into an
unconstrained problem.

Fminsearchbnd is used exactly like fminsearch,

A new metaheuristic optimization algorithm, called Cuckoo Search (CS), is fully implemented, and the vectorized version is given here. This code demonstrates how CS works for unconstrained optimization, which can easily be extended to solve...

Ok, yes, my expectation was that when I saw this, before I downloaded it I expected it to be a student's homework assigment. In fact, this is a reasonably carefully crafted tool.

One serious issue is that this code requires you to...

Demonstration of the gradient descent optimization algorithm with a fixed step size.
This example was developed for use in teaching optimization in graduate engineering courses. This example demonstrates how the gradient descent method can be...

The behaviour of applications sometimes depends on various parameters that can be chosen by the user through some GUI. Quite often, these parameters need take value in a predefined set. Parameters include for instance:

The number...

Equation fitting (kinetic constants and other parameter estimation):
- Classical model
- Klimpel model
- Kelsall model
- Modified Kelsall model
- Gamma model
- Fully mixed model


Demonstration of finding the minimum of a noisy function using gradient-based optimization.
This model was developed for use in teaching optimization in graduate engineering courses. It demonstrates one approach for attempting to find the...

settings = settingsdlg(...
'Description', 'This dialog will set the parameters used by FMINCON()',...
'title' , 'FMINCON() options',...
'separator' , 'Unconstrained/General',...
{'Tolerance X' ;'TolX' },...

Again, this SEEMS to be a reasonably crafted code. I wish it had better documentation, that explicitly said what the parameters did and what shape and size they should be. Some examples of use would be helpful. For example, this simple test case...