Documentation of tbx3sga
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Function Synopsis
GEAOPT = tbx3sga
Help text
ToolBoX function to define parameters for the Simple Genetic Algorithm (SGA)
This function defines parameters for the Simple Genetic Algorithm (SGA).
This includes the internal use of a binary representation (the variables can
be real, integer or binary).
Recombination/Crossover uses onepoint crossover and a crossover probability
of 0.7.
For mutation binary mutation must be used (because of the internal binary
representation). The mutation probability (default is 1) is internally
divided by the number of (internal) variables, thus only one binary value
per individual is mutated. Change this value appropriate. The used internal
value is presented on the screen at the beginning of the optimization.
Just one panmictic population is used.
The generation gap of selection is set to 1, thus no generation gap. Implicitly
the recombination/crossover probability of 0.7 works as an generation gap or
as elitist selection.
When using this parameter function, please compare to the other (more powerful)
parameter setting functions (tbx3real, tbx3comp, ...).
This parameter setting function is mainly provided to show you how to define
even the first and most simple genetic algorithm using the GEATbx. Can be used
for comparison or whatever you want. But these parameters are not recommended
for productive use  in nearly every realworld case they are not good.
Syntax: GEAOPT = tbx3sga
Input parameter:
no input parameters
Output parameter:
GEAOPT  Structure with newly defined options
See also: geamain2, geaoptset, tbx3bin, tbx3real, tbx3comp
CrossReference Information
This function calls 
This function is called by 


This document is part of
version 3.8 of the
GEATbx: Genetic and Evolutionary Algorithm Toolbox for use with Matlab 
www.geatbx.com.
The Genetic and Evolutionary Algorithm Toolbox is
not public domain.
© 19942006 Hartmut Pohlheim, All Rights Reserved,
(support@geatbx.com).