Computer Explorations of Fractals, Chaos,Complex Systems, and Adaptation

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 GABUMP Documentation

```

```

#### NAME

```       gabump - find a bump's peak with a genetic algorithm

```

#### SYNOPSIS

```       gabump -help
or
gabump [-target  double]  [-var  double]  [-size  integer]
[-len  integer]  [-gens  integer]  [-seed  integer]
[-crate double] [-mrate double]

```

#### DESCRIPTION

```       Use  a  genetic algorithm to find the maximum of a single-
humped function that is centered at a user-specified loca-
tion.  This program serves as an example of how GAs can be
used to optimize functions which  take  a  floating  point
argument.  Reproduction  of  strings entails crossover and
mutation with strings being selected based on fitness.

```

#### OPTIONS

```       -target double
Target value for function.

-var double
Variance of bump.

-size integer
Population size.

-len integer
DNA length.

-gens integer
Number of generations.

-seed integer
Random seed.

-crate double
Crossover rate.

-mrate double
Mutation rate.

```

#### MISCELLANY

```       The bit strings are converted to  floating  point  numbers
with  the  formula  (8  *  int(string)  / 2^len - 4) where
int(string) is the  integer  value  of  a  binary  string.
Thus, all numbers are forced to be between -4 and 4.

A  more  sophisticated GA encoding would use Gray codes to
represent the floating point numbers  which  arguably  are
better behaved under mutation.

```

#### BUGS

```       No  sanity  checks  are performed to make sure that any of
the options make sense.

```

#### AUTHOR

```       Copyright (c) 1997, Gary William Flake.

Permission granted for any use according to  the  standard
GNU ``copyleft'' agreement provided that the author's com-
ments are neither modified nor removed.   No  warranty  is
given or implied.

```