GEATbx.com

GEATbx - The Genetic and Evolutionary Algorithm Toolbox for Matlab

The Genetic and Evolutionary Algorithm Toolbox provides global optimization capabilities in Matlab to solve problems not suitable for traditional optimization approaches. Are you looking for a sophisticated way of solving your problem in case it has no derivatives, is discontinuous, stochastic, non-linear or has multiple minima or maxima? The GEATbx should be your method of choice!

Powerful genetic and evolutionary algorithms find solutions to your problems - and it's easy to use! Numerous ready to run examples and demonstrations give you a head start in setting up your problem, selecting the appropriate optimization algorithm and monitoring the state and progress of the optimization. This enables beginners and advanced users to achieve results fast.

In order to solve large and complex problems, the GEATbx contains extensions that are needed especially for the optimization of real world problems.

• visualization of the state and progress of your optimization,
• multi-objective optimization,
• constraint handling,
• problem-specific initialization and visualization.
• multi-strategy and multi-population support.

The complete toolbox is written in the open Matlab language (m files). This will enable you to inspect all examples, all demonstrations, and all functions. The toolbox can easily be modified or extended by your own custom functions.

The GEATbx comes with complete documentation.

Using the included demonstrations, the tutorial will guide you from your first optimizations to the implementation of your own objective functions and the selection of an appropriate optimization algorithm. With a few steps you can start solving your problems.
All aspects of the GEATbx will be explained in the Introduction to Evolutionary Algorithms, the Options and Parameter documentation and the description of Example functions.

The ready-to-run examples include:

• parameter optimization problems (controller optimization, engine control, climate control, parameter estimation, function optimization, ...),
• ordering problems (scheduling - TSP, VRP, JSSP, ...),
• constraint problems,
• discrete and binary problems (feature selection, knapsack, ...),
• many of the standard single and multi-objective benchmark functions (DeJong, Rosenbrock, Rastrigin, Griewangk, Schwefel, Auckley, Deb, Zitzler, Fonseca, ...)
• and many more can be solved using the GEATbx.

Here is what you get when you order the GEATbx!

1. The complete source code (m-files) of the GEATbx, runs on any Matlab platform (Matlab 6.1, 6.5, 7.x, R2006a, R2006b and newer).
2. 19 ready-to-run demonstrations,
3. 54 ready-to-run example functions,
4. step-by-step instructions on how to setup your optimization (Tutorial),
5. an Introduction to Evolutionary Algorithms explaining genetic and evolutionary algorithms,
6. extensive documentation of the evolutionary algorithm options for fine-tuning your optimizations,

In 12 years of GEATbx development we have solved countless complex optimization problems using the GEATbx and helped many other users tackling theirs. Our own and the other GEATbx users requirements have been incorporated in the continuous development of the GEATbx. The advanced features are a result of these longtime experiences.

On the one hand you can quickly setup a problem and run the optimization. On the other hand, when your needs grow and your problem gets larger and more difficult, the GEATbx still provides the features you need to solve your optimization problem successfully. You can concentrate on the solution of your problem; the GEATbx will do the optimization work and provides the tools you need for this.

Beside academic pricing we also provide special offers for classroom licenses, multi-user and site licenses. GEATbx Prices details conditions and prices on the different options.

Evaluate first and pay if you are satisfied!
If you want to evaluate the GEATbx, please refer to the Evaluation page for all the necessary information.

The Contact page provides details about technical support.

Download

On the Download page we offer free versions of the documentation of the GEATbx (free Introduction to Evolutionary Algorithms, the Tutorial for the GEATbx, ...). The documents are available in pdf and html format.
A number of Matlab m-files for everyday work is available too.

Other EA implementations

Over the years we collected links to other implementations of Evolutionary Algorithms in Matlab. This is a good starting point for comparing other implementations with the capabilities of the GEATbx.