Category Intelligent Software>Genetic Algorithm Systems/Tools

Abstract GEATbx (The Genetic and Evolutionary Algorithm Toolbox for Matlab) provides global optimization capabilities in Matlab (see Note 1) 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, and non-linear or has multiple minima or maxima? The GEATbx should be your method of choice!

Advanced 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.

GEATbx can be used by:

1) Engineers solving real-world problems;

2) Researchers comparing and developing new algorithms and test functions;

3) Students becoming acquainted with evolutionary algorithms.

In order to solve large and complex problems, the GEATbx contains extensions that are needed especially for the optimization of real world problems, which include: 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 be modified or extended by your own custom functions.

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.

GEATbx features/capabilities include:

1) High level functions to all operators.

2) Broad class of operators --

3) Complete support of multi-objective optimization --

4) Population models: global model, regional model (multiple subpopulations) and local model (local selection and reinsertion, different neighborhood structures).

5) Migration (regional model): unrestricted, ring, neighborhood.

6) Reinsertion: global, regional and local.

7) Multiple strategy support.

8) Real, integer and binary (linear and logarithmic scaling, gray coding) variable representation.

9) Sophisticated visualization.

10) Comfortable monitoring and storing of results.

11) Incorporation of problem specific knowledge (special initialization and problem specific visualization).

12) The GEATbx can be completely compiled into C/C++ Code using the Matlab Compiler.

13) Fully compatible with Matlab 5.3, 6.0, 6.1, 6.5, 7.1 (and probably newer versions).

Note 1: MATLAB is a high-level language and interactive environment that enables you to perform computationally intensive tasks faster than with traditional programming languages such as C, C++, and FORTRAN.

System Requirements

GEATbx requires Matlab 5.3 or a more recent version, already tested/used under Matlab 5.3, 6.0, 6.1, 6.5.1, 7.0, 7.1).

No platform dependence (runs on Windows, Linux, Solaris, ... without any changes).


Manufacturer Web Site GEATbx

Price Contact manufacturer.

G6G Abstract Number 20146

G6G Manufacturer Number 101180