Algorithm-Evolutionary-Fitness
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* lib/Algorithm/Evolutionary/Op/VectorCrossover.pm (apply): Fixed
bug: the incoming parent was modified along with the offspring.
2012-07-10 Juan J. Merelo Guervós <jjmerelo@gmail.com>
* MANIFEST: Eliminating pod.t also in production code.
2012-07-09 Juan J. Merelo Guervós <jjmerelo@gmail.com>
* MANIFEST: Eliminated pod-coverage.t, which is not needed for
production and causes errors in some systems.
2012-07-08 Juan J. Merelo Guervós <jjmerelo@gmail.com>
* MANIFEST: Adding missing test files
* lib/Algorithm/Evolutionary.pm: Starting a maintenance version,
which will include the bugs fixed since last summer.
Since there's a bug fix, I think I'm going for full 0.78...
2012-05-21 Juan J. Merelo Guervós <jjmerelo@gmail.com>
* lib/Algorithm/Evolutionary/Wheel.pm (spin): Changed spin
implementation to make it faster and more efficient. It was
sucking time out of mastermind EAs
2010-09-25 Juan J. Merelo <jmerelo@sheldon>
* lib/Algorithm/Evolutionary/Fitness/Rastrigin.pm (Rastrigin):
Fixed formula
* lib/Algorithm/Evolutionary.pm: Starting 0.74_1 with cosmetic
changes and an attempt to fix sporadic test errors.
2010-09-24 Juan Julian Merelo Guervos <jmerelo@usuario-desktop>
* lib/Algorithm/Evolutionary/Fitness/Rastrigin.pm (Rastrigin): Added first floating-point fitness func.
* lib/Algorithm/Evolutionary/Utils.pm (random_number_array): Added this function
* lib/Algorithm/Evolutionary/Individual/BitString.pm (from_string): Added from_string ctor
* lib/Algorithm/Evolutionary/Individual/String.pm (from_string): Changed name and slightly modified
Starting documentation revision for developer releases.
* lib/Algorithm/Evolutionary/Op/EDA_step.pm (apply): Added new
module implementing estimation of distribution algorithms; added
test and example in /examples
2009-07-30 Juan Julian Merelo Guervos <jmerelo@geneura.ugr.es>
* lib/Algorithm/Evolutionary.pm: Moved a GUI example to the
scripts dir so that it's installed automatically. Expanded
documentation to reflect that. Fixed also error (population
explosion) in Easy_MO.
2009-07-28 Juan Julian Merelo Guervos <jmerelo@geneura.ugr.es>
* lib/Algorithm/Evolutionary.pm: Starting 0.70_1 with the
classical documentation fixes.
* MANIFEST: 0.70 fixes a bug in Easy.pm and those derived from it:
last population element was not eliminated. An animated GIF output
has been added, and a bug in Makefile.PL that caused problems with
* lib/Algorithm/Evolutionary.pm (import): 0.69_1 fixed some
problems with missing prerrequisites in the test programs, and
some copy/paste stuff left from creating new modules. 0.70 starts
with the intention of finally having a GUI.
2009-07-24 <jmerelo@localhost.localdomain>
* lib/Algorithm/Evolutionary.pm: 0.68 was shortlived, but 0.69
more or less the same. 0.69 included missing file and fixed some
docs errors; 0.69_1 starts with the same objective, let's see how
it ends.
2009-07-24 Juan Julian Merelo Guervos <jmerelo@geneura.ugr.es>
* TODO: 0.68 ends with several new test functions added (Trap,
ECC), and finally a multiobjective evolutionary algorithm, not
very good, but in working order.
2009-03-29 <jmerelo@localhost.localdomain>
lib/Algorithm/Evolutionary/Fitness/ECC.pm view on Meta::CPAN
my $p_peaks = Algorithm::Evolutionary::Fitness::ECC->new( $number_of_codewords, $min_distance );
=head1 DESCRIPTION
Extracted from article "Effects of scale-free and small-world topologies on binary coded self-adaptive CEA", by Giacobini et al [Ga]. Quoting:
" The ECC problem was presented in
[MW]. We will consider a three-tuple (n, M, d), where n is the length of each codeword
(number of bits), M is the number of codewords, and d is the minimum Hamming
distance between any pair of codewords. Our objective will be to find a code which
has a value for d as large as possible (reflecting greater tolerance to noise and errors),
given previously fixed values for n and M . The problem we have studied is a simplified
version of that in [MW]. In our case we search half of the codewords (M/2) that will
compose the code, and the other half is made up by the complement of the codewords
computed by the algorithm"
[Ga] Mario Giacobini, Mike Preuss, Marco Tomassini: Effects of Scale-Free and Small-World Topologies on Binary Coded Self-adaptive CEA. EvoCOP 2006: 86-98.
[MW] F. J. MacWilliams and N. J. A. Sloane. The Theory of Error-Correcting Codes. North-
Holland, Amsterdam, 1977.
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