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Deterministic unconstrained optimization method using Powell.



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.

Pattern...



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...



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...



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...



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 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...



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...



Algorithm for solving search and optimization problems.



A few popular metaheuristic algorithms are included, such as the particle swarm optimization, firefly algorithm, harmony search and others.



M-files accompanying the " Genetic Algorithms & New Optimization Methods in MATLAB " webinar.

These files provide what you need to run the two demos: Optimization of non-smooth objective function, and Optimization of a...



Particle swarm optimization is a technique used in many control systems application. Here i used the PSO in PID controller tuning



An animated simulation of Particles in 2D searching for a global minima of a simple function using Particle Swarm Optimization algorithm



The files in this folder solve the optimization case studies described in the paper "VaR vs CVaR in Risk Management and Optimization" by Sarykalin,S., Serraino,G., and Uryasev,S., in Tutorials in Operations Research, INFORMS 2008...



This upload contains a hybrid Particle Swarm Optimization algorithm for functions in the real space. An options file is also provided, which lets the user fully parameterize the process. The hybrid function used is the @fminsearch, which is...



This demo shows how to use MATLAB, Optimization Toolbox, and Genetic Algorithm and Direct Search Toolbox to optimize the design of a double wishbone suspension system.

Note: You will need to have the following products installed in...



GANSO is a programming library for global and nonsmooth, nonlinear optimization. Unlike local methods (e.g., quasi-Newton), global optimization methods aim at locating the absolute minimum of a function, not the nearest stationary point. GANSO...



A demo program of image edge detection using ant colony optimization.



Fiels from the webinar: Speeding up optimization problems with parallel computing



This is a wrapper function to solve optimization problems (using FMINCON) of the form:

min w.r.t. X of
CostFunc(X) = beta*(W_ls*F(X)) + (1 - beta)*(max(W_mm*F(X)))

subject to:
A*X <= B, Aeq*X = Beq (linear...