Algorithm-Evolutionary
view release on metacpan or search on metacpan
interactive use in the most ordinary way, to print or display an
announcement including an appropriate copyright notice and a
notice that there is no warranty (or else, saying that you provide
a warranty) and that users may redistribute the program under
these conditions, and telling the user how to view a copy of this
License. (Exception: if the Program itself is interactive but
does not normally print such an announcement, your work based on
the Program is not required to print an announcement.)
These requirements apply to the modified work as a whole. If
identifiable sections of that work are not derived from the Program,
and can be reasonably considered independent and separate works in
themselves, then this License, and its terms, do not apply to those
sections when you distribute them as separate works. But when you
distribute the same sections as part of a whole which is a work based
on the Program, the distribution of the whole must be on the terms of
this License, whose permissions for other licensees extend to the
entire whole, and thus to each and every part regardless of who wrote it.
Thus, it is not the intent of this section to claim rights or contest
your rights to work written entirely by you; rather, the intent is to
exercise the right to control the distribution of derivative or
collective works based on the Program.
In addition, mere aggregation of another work not based on the Program
with the Program (or with a work based on the Program) on a volume of
a storage or distribution medium does not bring the other work under
the scope of this License.
3. You may copy and distribute the Program (or a work based on it,
years, to give any third party, for a charge no more than your
cost of physically performing source distribution, a complete
machine-readable copy of the corresponding source code, to be
distributed under the terms of Sections 1 and 2 above on a medium
customarily used for software interchange; or,
c) Accompany it with the information you received as to the offer
to distribute corresponding source code. (This alternative is
allowed only for noncommercial distribution and only if you
received the program in object code or executable form with such
an offer, in accord with Subsection b above.)
The source code for a work means the preferred form of the work for
making modifications to it. For an executable work, complete source
code means all the source code for all modules it contains, plus any
associated interface definition files, plus the scripts used to
control compilation and installation of the executable. However, as a
special exception, the source code distributed need not include
anything that is normally distributed (in either source or binary
form) with the major components (compiler, kernel, and so on) of the
operating system on which the executable runs, unless that component
otherwise) that contradict the conditions of this License, they do not
excuse you from the conditions of this License. If you cannot
distribute so as to satisfy simultaneously your obligations under this
License and any other pertinent obligations, then as a consequence you
may not distribute the Program at all. For example, if a patent
license would not permit royalty-free redistribution of the Program by
all those who receive copies directly or indirectly through you, then
the only way you could satisfy both it and this License would be to
refrain entirely from distribution of the Program.
If any portion of this section is held invalid or unenforceable under
any particular circumstance, the balance of the section is intended to
apply and the section as a whole is intended to apply in other
circumstances.
It is not the purpose of this section to induce you to infringe any
patents or other property right claims or to contest validity of any
such claims; this section has the sole purpose of protecting the
integrity of the free software distribution system, which is
implemented by public license practices. Many people have made
generous contributions to the wide range of software distributed
through that system in reliance on consistent application of that
system; it is up to the author/donor to decide if he or she is willing
to distribute software through any other system and a licensee cannot
impose that choice.
This section is intended to make thoroughly clear what is believed to
be a consequence of the rest of this License.
8. If the distribution and/or use of the Program is restricted in
certain countries either by patents or by copyrighted interfaces, the
original copyright holder who places the Program under this License
may add an explicit geographical distribution limitation excluding
those countries, so that distribution is permitted only in or among
countries not thus excluded. In such case, this License incorporates
the limitation as if written in the body of this License.
make
make test
make install
```
Issue first
cpanm --installdeps .
if the upstream dependencies are not installed (which they are wont to
do). Check also the DEPENDENCIES section below for non-perl dependencies.
## WARNING
Since evolutionary algorithms are stochastic optimization algorithms,
some tests, specially in the `general.t` file, might fail; running
them again might yield a different result. If your installation (from
CPAN, CPANPLUS or cpanminus) fails for this reason, run a force install, or try
to `make install` disregarding the tests.
lib/Algorithm/Evolutionary/Hash_Wheel.pm view on Meta::CPAN
my %probs = %$probs_hashref;
my $self = { _accProbs => [] };
my $acc = 0;
for ( sort keys %probs ) { $acc += $probs{$_};}
for ( sort keys %probs ) { $probs{$_} /= $acc;} #Normalizes array
#Now creates the accumulated array, putting the accumulated
#probability in the first element arrayref element, and the object
#in the second
my $aux = 0;
for ( sort keys %probs ) {
push @{$self->{_accProbs}}, [$probs{$_} + $aux,$_ ];
$aux += $probs{$_};
}
bless $self, $class;
return $self;
}
lib/Algorithm/Evolutionary/Op/CX.pm view on Meta::CPAN
Applies Algorithm::Evolutionary::Op::CX operator to a "Chromosome", a bitstring, really. Can be
applied only to I<victims> with the C<_bitstring> instance variable; but
it checks before application that both operands are of type
L<Individual::Vector|Algorithm::Evolutionary::Individual::Vector>.
=cut
sub apply ($$;$){
my $self = shift;
my $p1 = shift || croak "No victim here!"; #first parent
my $p2 = shift || croak "No victim here!"; #second parent
my $child=$p1->clone(); #Child
my $i; #Iterator
my $j; #Iterator
my $changed;
#Check parents type and size
croak "Incorrect type ".(ref $p1) if !$self->check($p1);
croak "Incorrect type ".(ref $p2) if !$self->check($p2);
croak "Algorithm::Evolutionary::Op::CX Error: Parents don't have the same size " if ($p1->length() != $p2->length() );
lib/Algorithm/Evolutionary/Op/CX.pm view on Meta::CPAN
last;
}
}
#Look if the next element in cycle was found
if ($found) {
$child->Atom($found, $p1->Atom($found));
# print "Found $found valor ", $child->Atom($found), "\n";
$i=$found;
$changed++;
}
else { #End of the cycle, get the genes from the second parent
$child->Atom(0, $p1->Atom(0) ); $changed++;
for ($i=1;( $i < $leng ) && ( $changed < $leng ) ; $i++) {
if ($child->Atom($i) eq $no ) {
# print "Cambiando $i valor ", $p2->Atom($i), "\n";
$child->Atom($i,$p2->Atom($i));
$changed++;
}
}
}
}#End-while
lib/Algorithm/Evolutionary/Op/CanonicalGA.pm view on Meta::CPAN
L<Algorithm::Evolutionary::Op::Base|Algorithm::Evolutionary::Op::Base>
=head1 DESCRIPTION
The canonical classical genetic algorithm evolves a population of
bitstrings until they reach the optimum fitness. It performs mutation
on the bitstrings by flipping a single bit, crossover interchanges a
part of the two parents.
The first operator should be unary (a la mutation) and the second
binary (a la crossover) they will be applied in turn to couples of the
population.
=head1 METHODS
=cut
package Algorithm::Evolutionary::Op::CanonicalGA;
use lib qw(../../..);
lib/Algorithm/Evolutionary/Op/CanonicalGA.pm view on Meta::CPAN
use base 'Algorithm::Evolutionary::Op::Easy';
# Class-wide constants
our $APPLIESTO = 'ARRAY';
our $ARITY = 1;
=head2 new( $fitness[, $selection_rate][,$operators_ref_to_array] )
Creates an algorithm, with the usual operators. Includes a default mutation
and crossover, in case they are not passed as parameters. The first
element in the array ref should be an unary, and the second a
binary operator.
=cut
sub new {
my $class = shift;
my $self = {};
$self->{_eval} = shift || croak "No eval function found";
$self->{_selrate} = shift || 0.4;
if ( @_ ) {
lib/Algorithm/Evolutionary/Op/Canonical_GA_NN.pm view on Meta::CPAN
L<Algorithm::Evolutionary::Op::Base|Algorithm::Evolutionary::Op::Base>
=head1 DESCRIPTION
The canonical classical genetic algorithm evolves a population of
bitstrings until they reach the optimum fitness. It performs mutation
on the bitstrings by flipping a single bit, crossover interchanges a
part of the two parents.
The first operator should be unary (a la mutation) and the second
binary (a la crossover) they will be applied in turn to couples of the
population.
This is a fast version of the canonical GA, useful for large
populations, since it avoids the expensive rank operation. Roulette
wheel selection, still, is kind of slow.
=head1 METHODS
=cut
lib/Algorithm/Evolutionary/Op/Canonical_GA_NN.pm view on Meta::CPAN
use base 'Algorithm::Evolutionary::Op::Easy';
# Class-wide constants
our $APPLIESTO = 'ARRAY';
our $ARITY = 1;
=head2 new( [ $selection_rate][,$operators_ref_to_array] )
Creates an algorithm, with the usual operators. Includes a default
mutation and crossover, in case they are not passed as parameters. The
first element in the array ref should be an unary, and the second a
binary operator. This binary operator must accept parameters by
reference, not value; it will modify them. For the time being, just
L<Algorithm::Evolutionary::Op::QuadXOver> works that way.
=cut
sub new {
my $class = shift;
my $self = {};
$self->{'_selrate'} = shift || 0.4;
lib/Algorithm/Evolutionary/Op/Crossover.pm view on Meta::CPAN
use strict;
use warnings;
=head1 NAME
Algorithm::Evolutionary::Op::Crossover - n-point crossover
operator; puts fragments of the second operand into the first operand
=head1 SYNOPSIS
#Create from XML description using EvoSpec
my $xmlStr3=<<EOC;
<op name='Crossover' type='binary' rate='1'>
<param name='numPoints' value='3' /> #Max is 2, anyways
</op>
EOC
lib/Algorithm/Evolutionary/Op/Easy.pm view on Meta::CPAN
my $codehash = shift || croak "No code here";
my $opshash = shift || croak "No ops here";
$self->{_selrate} = $hashref->{selrate};
for ( keys %$codehash ) {
$self->{"_$_"} = eval "sub { $codehash->{$_} } " || carp "Error compiling fitness function: $! => $@";
}
$self->{_ops} =();
for ( keys %$opshash ) {
#First element of the array contains the content, second the rate.
push @{$self->{_ops}},
Algorithm::Evolutionary::Op::Base::fromXML( $_, $opshash->{$_}->[1], $opshash->{$_}->[0] );
}
}
=head2 apply( $population )
Applies the algorithm to the population; checks that it receives a
ref-to-array as input, croaks if it does not. Returns a sorted,
culled, evaluated population for next generation.
lib/Algorithm/Evolutionary/Op/Easy_MO.pm view on Meta::CPAN
my $codehash = shift || croak "No code here";
my $opshash = shift || croak "No ops here";
$self->{_selrate} = $hashref->{selrate};
for ( keys %$codehash ) {
$self->{"_$_"} = eval "sub { $codehash->{$_} } " || carp "Error compiling fitness function: $! => $@";
}
$self->{_ops} =();
for ( keys %$opshash ) {
#First element of the array contains the content, second the rate.
push @{$self->{_ops}},
Algorithm::Evolutionary::Op::Base::fromXML( $_, $opshash->{$_}->[1], $opshash->{$_}->[0] );
}
}
=head2 apply( $population )
Applies the algorithm to the population; checks that it receives a
ref-to-array as input, croaks if it does not. Returns a sorted,
lib/Algorithm/Evolutionary/Op/Inverover.pm view on Meta::CPAN
=cut
sub create {
my $class = shift;
my $self;
bless $self, $class;
return $self;
}
=head2 apply( $first, $second )
Applies Algorithm::Evolutionary::Op::Inverover operator to a
"Chromosome". Can be applied to anything with the Atom method.
=cut
sub apply ($$$){
my $self = shift;
my $p1 = shift || croak "No victim here!"; #first parent
my $p2 = shift || croak "No victim here!"; #second parent
my $child=$p1->clone(); #Clone S' (child) from First parent
my $i; #Iterator
#Check parents type and size
croak "Incorrect type ".(ref $p1) if !$self->check($p1);
croak "Incorrect type ".(ref $p2) if !$self->check($p2);
croak "Inver-over Error: Parents haven't sime size " if ($p1->length() != $p2->length() );
my $leng=$p1->length(); #Chrom length
lib/Algorithm/Evolutionary/Op/Inverover.pm view on Meta::CPAN
#Build Algorithm::Evolutionary::Op::Inverover child
while ( 1 )
{
if (rand() <= $self->rate)
{ #Select c' (c2) from the remaining cities of S'(child)
$c2=int( rand( $leng - $c ) + $c);
$c2+=2 if (($c2 == $c+1) && ($c2 < $leng -2) );
}
else
{ #Assign to c' (c2) the 'next' atom to the atom c in the second parent
for ($c2=0;$c2 < $leng; $c2++)
{ last if ( $child->Atom($c) == $p2->Atom($c2) );}
$c2= ($c2+1) % $leng;
}
# print "\nc= $c c2= $c2 lneg= $leng atom(c2)=".$child->Atom($c2)." atom(c+1)=".$child->Atom(($c+1) % $leng)."\n";
#Check if finish
last if ( ($child->Atom($c2) == $child->Atom( ($c+1)% $leng) ) || ($c+1==$leng) );
# Inverse the section from the next atom of atom c to the atom c' (c2) in S' (child)
for ($i=0;$i+$c <= ($c2/2) ; $i++)
{
# print "\n\tCambio de Atom(".($i+$c+1).")=".$child->Atom($i+$c+1)." por Atom(".($c2-$i).")=".$child->Atom($c2-$i);
my $aux=$child->Atom($i+$c+1);
$child->Atom($i+$c+1,$child->Atom($c2-$i) );
$child->Atom(($c2-$i),$aux);
}
$c=$c2;
}#End-while
( run in 0.744 second using v1.01-cache-2.11-cpan-39bf76dae61 )