ga/ 000755 000767 000000 00000000000 11737425143 012555 5 ustar 00slackydeb wheel 000000 000000 ga/COPYING 000644 000767 000000 00000043077 11737424747 013634 0 ustar 00slackydeb wheel 000000 000000 GNU GENERAL PUBLIC LICENSE
Version 2, June 1991
Copyright (C) 1989, 1991 Free Software Foundation, Inc.
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
Preamble
The licenses for most software are designed to take away your
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General Public License applies to most of the Free Software
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using it. (Some other Free Software Foundation software is covered by
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When we speak of free software, we are referring to freedom, not
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GNU GENERAL PUBLIC LICENSE
TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
0. This License applies to any program or other work which contains
a notice placed by the copyright holder saying it may be distributed
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END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
convey the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
Copyright (C)
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program; if not, see .
Also add information on how to contact you by electronic and paper mail.
If the program is interactive, make it output a short notice like this
when it starts in an interactive mode:
Gnomovision version 69, Copyright (C) year name of author
Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, the commands you use may
be called something other than `show w' and `show c'; they could even be
mouse-clicks or menu items--whatever suits your program.
You should also get your employer (if you work as a programmer) or your
school, if any, to sign a "copyright disclaimer" for the program, if
necessary. Here is a sample; alter the names:
Yoyodyne, Inc., hereby disclaims all copyright interest in the program
`Gnomovision' (which makes passes at compilers) written by James Hacker.
, 1 April 1989
Ty Coon, President of Vice
This General Public License does not permit incorporating your program into
proprietary programs. If your program is a subroutine library, you may
consider it more useful to permit linking proprietary applications with the
library. If this is what you want to do, use the GNU Library General
Public License instead of this License.
ga/doc/ 000755 000767 000000 00000000000 11737424747 013333 5 ustar 00slackydeb wheel 000000 000000 ga/INDEX 000644 000767 000000 00000000402 11737424747 013354 0 ustar 00slackydeb wheel 000000 000000 ga >> Genetic Algorithm
Genetic Algorithm
ga
gaoptimset
Creation
gacreationuniform
Fitness Scaling
fitscalingrank
Selection
selectionstochunif
Crossover
crossoverscattered
Mutation
mutationgaussian
Utility
rastriginsfcn
Miscellaneous
test_ga
ga/inst/ 000755 000767 000000 00000000000 11737424747 013543 5 ustar 00slackydeb wheel 000000 000000 ga/NEWS 000644 000767 000000 00000001610 11737424747 013263 0 ustar 00slackydeb wheel 000000 000000 Summary of important user-visible changes for releases of the ga package
===============================================================================
ga-0.10.0 Release Date: 2012-04-06 Release Manager: Luca Favatella
===============================================================================
** Remove dependency on the "communications" package and require
Octave version 3.4.0 (or better). The "communications" package was
used only for its "randint" function; now the "randi" function,
introduced in Octave 3.4.0, is used instead.
** Reorganize the unit test suite. All available tests can be
executed by running "test_ga". Fix bug #3287917 (Debian bug
#622929).
** Rename the package from "Genetic Algorithm and Direct Search" to
"Genetic Algorithm" as only the Genetic Algorithm is implemented.
Direct Search will not be implemented in the foreseeable future.
ga/inst/__ga_crossoverfcn__.m 000644 000767 000000 00000002433 11737424747 017702 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 1.3.3
function xoverKids = __ga_crossoverfcn__ (parents, options, nvars, FitnessFcn,
unused,
thisPopulation)
## preconditions
nc_parents = columns (parents);
if (rem (nc_parents, 2) != 0)
error ("'parents' must have an even number of columns");
endif
xoverKids(1:(nc_parents / 2), 1:nvars) = options.CrossoverFcn \
(parents(1, 1:nc_parents), options, nvars, FitnessFcn,
unused,
thisPopulation(:, 1:nvars));
endfunction ga/inst/__ga_initial_population__.m 000644 000767 000000 00000007237 11737424747 021100 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008, 2010 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## -*- texinfo -*-
## @deftypefn{Function File} {@var{Population} =} __ga_initial_population__ (@var{GenomeLength}, @var{FitnessFcn}, @var{options})
## Create an initial population.
##
## @seealso{__ga_problem__}
## @end deftypefn
## Author: Luca Favatella
## Version: 3.3
#TODO consider PopulationSize as a
#vector for multiple subpopolations
function Population = \
__ga_initial_population__ (GenomeLength, FitnessFcn, options)
if (isempty (options.InitialPopulation))
Population(1:options.PopulationSize, 1:GenomeLength) = \
options.CreationFcn (GenomeLength, FitnessFcn, options);
else
if (columns (options.InitialPopulation) != GenomeLength) ## columns (InitialPopulation) > 0
error ("nonempty 'InitialPopulation' must have 'GenomeLength' columns");
else ## rows (InitialPopulation) > 0
nrIP = rows (options.InitialPopulation);
if (nrIP > options.PopulationSize)
error ("nonempty 'InitialPopulation' must have no more than \
'PopulationSize' rows");
elseif (nrIP == options.PopulationSize)
Population(1:options.PopulationSize, 1:GenomeLength) = \
options.InitialPopulation;
else # rows (InitialPopulation) < PopulationSize
## create a complete new population, and then select only needed
## individuals (creating only a partial population is difficult)
CreatedPopulation(1:options.PopulationSize, 1:GenomeLength) = \
options.CreationFcn (GenomeLength, FitnessFcn, options);
Population(1:options.PopulationSize, 1:GenomeLength) = vertcat \
(options.InitialPopulation(1:nrIP, 1:GenomeLength),
CreatedPopulation(1:(options.PopulationSize - nrIP),
1:GenomeLength));
endif
endif
endif
endfunction
%!test
%! GenomeLength = 2;
%! options = gaoptimset ();
%! Population = __ga_initial_population__ (GenomeLength, @rastriginsfcn, options);
%! assert (size (Population), [options.PopulationSize, GenomeLength]);
%!test
%! GenomeLength = 2;
%! options = gaoptimset ("InitialPopulation", [1, 2; 3, 4; 5, 6]);
%! Population = __ga_initial_population__ (GenomeLength, @rastriginsfcn, options);
%! assert (size (Population), [options.PopulationSize, GenomeLength]);
## nonempty 'InitialPopulation' must have 'GenomeLength' columns
%!error
%! GenomeLength = 2;
%! options = gaoptimset ("InitialPopulation", [1; 3; 5]);
%! __ga_initial_population__ (GenomeLength, @rastriginsfcn, options);
%!error
%! GenomeLength = 2;
%! options = gaoptimset ("InitialPopulation", [1, 1, 1; 3, 3, 3; 5, 5, 5]);
%! __ga_initial_population__ (GenomeLength, @rastriginsfcn, options);
## nonempty 'InitialPopulation' must have no more than 'PopulationSize' rows
%!error
%! GenomeLength = 2;
%! options = gaoptimset ("InitialPopulation", [1, 2; 3, 4; 5, 6], "PopulationSize", 2);
%! __ga_initial_population__ (GenomeLength, @rastriginsfcn, options);
ga/inst/__ga_mutationfcn__.m 000644 000767 000000 00000002267 11737424747 017522 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 1.3
function mutationChildren = \
__ga_mutationfcn__ (parents, options, nvars, FitnessFcn,
state, thisScore,
thisPopulation)
mutationChildren(1:(columns (parents)), 1:nvars) = \
options.MutationFcn{1, 1} (parents(1, :), options, nvars, FitnessFcn,
state, thisScore,
thisPopulation(:, 1:nvars));
endfunction ga/inst/__ga_popinitrange__.m 000644 000767 000000 00000002141 11737424747 017661 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 2.1
function [LB UB] = __ga_popinitrange__ (PopInitRange, nvars)
switch (columns (PopInitRange))
case 1
tmpPIR(1:2, 1:nvars) = PopInitRange(1:2, 1) * ones (1, nvars);
case nvars
tmpPIR(1:2, 1:nvars) = PopInitRange(1:2, 1:nvars);
endswitch
LB(1, 1:nvars) = tmpPIR(1, 1:nvars);
UB(1, 1:nvars) = tmpPIR(2, 1:nvars);
endfunction ga/inst/__ga_problem__.m 000644 000767 000000 00000010240 11737424747 016621 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 5.9
function [x fval exitflag output population scores] = __ga_problem__ (problem)
## first instruction
state.StartTime = time ();
## second instruction
output = struct ("randstate", rand ("state"),
"randnstate", randn ("state"));
## instructions not to be executed at each generation
state.Population(1:problem.options.PopulationSize, 1:problem.nvars) = \
__ga_initial_population__ (problem.nvars,
problem.fitnessfcn,
problem.options);
state.Generation = 0;
private_state = __ga_problem_private_state__ (problem.options);
state.Selection = __ga_problem_state_selection__ (private_state,
problem.options);
## instructions to be executed at each generation
state = __ga_problem_update_state_at_each_generation__ (state, problem,
private_state);
NextPopulation = zeros (problem.options.PopulationSize, problem.nvars);
while (! __ga_stop__ (problem, state)) ## fix a generation
## elite
if (private_state.ReproductionCount.elite > 0)
[trash IndexSortedScores] = sort (state.Score);
NextPopulation(state.Selection.elite, 1:problem.nvars) = \
state.Population \
(IndexSortedScores(1:private_state.ReproductionCount.elite, 1),
1:problem.nvars);
endif
## selection for crossover and mutation
parents(1, 1:private_state.nParents) = __ga_selectionfcn__ \
(state.Expectation, private_state.nParents, problem.options);
## crossover
if (private_state.ReproductionCount.crossover > 0)
NextPopulation(state.Selection.crossover, 1:problem.nvars) = \
__ga_crossoverfcn__ \
(parents(1, private_state.parentsSelection.crossover),
problem.options, problem.nvars, problem.fitnessfcn,
false, ## unused
state.Population);
endif
## mutation
if (private_state.ReproductionCount.mutation > 0)
NextPopulation(state.Selection.mutation, 1:problem.nvars) = \
__ga_mutationfcn__ \
(parents(1, private_state.parentsSelection.mutation),
problem.options, problem.nvars, problem.fitnessfcn,
state, state.Score,
state.Population);
endif
## update state structure
state.Population(1:problem.options.PopulationSize,
1:problem.nvars) = NextPopulation;
state.Generation++;
state = __ga_problem_update_state_at_each_generation__ (state, problem,
private_state);
endwhile
[x fval exitflag output population scores] = \
__ga_problem_return_variables__ (state, problem);
endfunction
#state structure fields
#DONE state.Population
#DONE state.Score
#DONE state.Generation
#DONE state.StartTime
#state.StopFlag
#DONE state.Selection
#DONE state.Expectation
#DONE state.Best
#state.LastImprovement
#state.LastImprovementTime
#state.NonlinIneq
#state.NonlinEq ga/inst/__ga_problem_private_state__.m 000644 000767 000000 00000004142 11737424747 021557 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 1.1.1
function private_state = __ga_problem_private_state__ (options)
private_state.ReproductionCount.elite = options.EliteCount;
private_state.ReproductionCount.crossover = \
fix (options.CrossoverFraction *
(options.PopulationSize - options.EliteCount));
private_state.ReproductionCount.mutation = \
options.PopulationSize - \
(private_state.ReproductionCount.elite +
private_state.ReproductionCount.crossover);
assert (private_state.ReproductionCount.elite +
private_state.ReproductionCount.crossover +
private_state.ReproductionCount.mutation,
options.PopulationSize); ## DEBUG
private_state.parentsCount.crossover = \
2 * private_state.ReproductionCount.crossover;
private_state.parentsCount.mutation = \
1 * private_state.ReproductionCount.mutation;
private_state.nParents = \
private_state.parentsCount.crossover + \
private_state.parentsCount.mutation;
private_state.parentsSelection.crossover = \
1:private_state.parentsCount.crossover;
private_state.parentsSelection.mutation = \
private_state.parentsCount.crossover + \
(1:private_state.parentsCount.mutation);
assert (length (private_state.parentsSelection.crossover) +
length (private_state.parentsSelection.mutation),
private_state.nParents); ## DEBUG
endfunction ga/inst/__ga_problem_return_variables__.m 000644 000767 000000 00000002642 11737424747 022257 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 1.1
function [x fval exitflag output population scores] = \
__ga_problem_return_variables__ (state, problem)
[trash IndexMinScore] = min (state.Score);
x = state.Population(IndexMinScore, 1:problem.nvars);
fval = problem.fitnessfcn (x);
#TODO exitflag
## output.randstate and output.randnstate must be assigned at the
## start of the algorithm
output.generations = state.Generation;
#TODO output.funccount
#TODO output.message
#TODO output.maxconstraint
population = state.Population;
scores = state.Score;
endfunction ga/inst/__ga_problem_state_selection__.m 000644 000767 000000 00000002560 11737424747 022074 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 1.1.1
function Selection = __ga_problem_state_selection__ (private_state, options)
Selection.elite = 1:private_state.ReproductionCount.elite;
Selection.crossover = \
private_state.ReproductionCount.elite + \
(1:private_state.ReproductionCount.crossover);
Selection.mutation = \
private_state.ReproductionCount.elite + \
private_state.ReproductionCount.crossover + \
(1:private_state.ReproductionCount.mutation);
#assert (length (Selection.elite) +
# length (Selection.crossover) +
# length (Selection.mutation),
# options.PopulationSize); ##DEBUG
endfunction ga/inst/__ga_problem_update_state_at_each_generation__.m 000644 000767 000000 00000004233 11737424747 025247 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008, 2010 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 1.3.1
function state = \
__ga_problem_update_state_at_each_generation__ (state, problem,
private_state)
if ((state.Generation > 0) || isempty (problem.options.InitialScores))
state.Score(1:problem.options.PopulationSize, 1) = \
__ga_scores__ (problem, state.Population);
else ## (Generation == 0) && (! isempty (InitialScores))
nrIS = rows (problem.options.InitialScores);
#assert (rows (problem.options.InitialPopulation) <= problem.options.PopulationSize); ## DEBUG
if (nrIS <= rows (problem.options.InitialPopulation))
missing_rows = (nrIS+1):problem.options.PopulationSize;
state.Score(1:problem.options.PopulationSize, 1) = \
[problem.options.InitialScores(:, 1);
(__ga_scores__ (problem, state.Population(missing_rows, :)))
];
else
error ("rows (InitialScores) > rows (InitialPopulation)");
endif
endif
state.Expectation(1, 1:problem.options.PopulationSize) = \
problem.options.FitnessScalingFcn (state.Score, private_state.nParents);
state.Best(state.Generation + 1, 1) = min (state.Score);
endfunction
%!error
%! state.Generation = 0;
%! problem = struct ("fitnessfcn", @rastriginsfcn, "nvars", 2, "options", gaoptimset ("Generations", 10, "InitialScores", [0; 0; 0]));
%! unused = 0;
%! __ga_problem_update_state_at_each_generation__ (state, problem, unused); ga/inst/__ga_scores__.m 000644 000767 000000 00000004004 11737424747 016460 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008, 2010 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 5.7
function Scores = __ga_scores__ (problem, Population)
[nrP ncP] = size (Population);
switch problem.options.Vectorized
case "on" ## using vectorized evaluation
switch problem.options.UseParallel
case "always"
warning ("'Vectorized' option is 'on': ignoring 'UseParallel' option, even if it is 'always'");
case "never"
## Nothing.
otherwise
warning ("'Vectorized' option is 'on': ignoring invalid 'UseParallel' option value (it should be 'always' or 'never')");
endswitch
Scores = (problem.fitnessfcn (Population))(1:nrP, 1);
case "off" ## not using vectorized evaluation
switch problem.options.UseParallel
case "always" ## using parallel evaluation
error ("TODO: implement parallel evaluation of objective function");
case "never" ## using serial evaluation (i.e. loop)
tmp = zeros (nrP, 1);
for index = 1:nrP
tmp(index, 1) = problem.fitnessfcn (Population(index, 1:ncP));
endfor
Scores = tmp(1:nrP, 1);
otherwise
error ("'UseParallel' option must be 'always' or 'never'");
endswitch
otherwise
error ("'Vectorized' option must be 'on' or 'off'");
endswitch
endfunction
ga/inst/__ga_selectionfcn__.m 000644 000767 000000 00000001670 11737424747 017644 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 1.2
function parents = __ga_selectionfcn__ (expectation, nParents, options)
parents(1, 1:nParents) = \
options.SelectionFcn (expectation(1, :), nParents, options);
endfunction ga/inst/__ga_stop__.m 000644 000767 000000 00000002530 11737424747 016151 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## -*- texinfo -*-
## @deftypefn{Function File} {@var{stop} =} __ga_stop__ (@var{problem}, @var{state})
## Determine whether the genetic algorithm should stop.
##
## @seealso{__ga_problem__}
## @end deftypefn
## Author: Luca Favatella
## Version: 5.1
function stop = __ga_stop__ (problem, state)
Generations = \
(state.Generation >= problem.options.Generations);
TimeLimit = \
((time () - state.StartTime) >= problem.options.TimeLimit);
FitnessLimit = \
(state.Best(state.Generation + 1, 1) <= problem.options.FitnessLimit);
stop = (Generations ||
TimeLimit ||
FitnessLimit);
endfunction ga/inst/__gaoptimset_default_options__.m 000644 000767 000000 00000005307 11737424747 022155 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008, 2009, 2010 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 1.2.3
function default_options = __gaoptimset_default_options__ ()
default_options.CreationFcn = @gacreationuniform;
default_options.CrossoverFcn = @crossoverscattered;
default_options.CrossoverFraction = 0.8;
#default_options.Display = "final";
#default_options.DistanceMeasureFcn gamultiobj
default_options.EliteCount = 2;
default_options.FitnessLimit = -Inf;
default_options.FitnessScalingFcn = @fitscalingrank;
default_options.Generations = 100;
#default_options.HybridFcn = [];
#default_options.InitialPenalty = 10;
default_options.InitialPopulation = [];
default_options.InitialScores = [];
#default_options.MigrationDirection = "forward";
#default_options.MigrationFraction = 0.2;
#default_options.MigrationInterval = 20;
default_options.MutationFcn = {@mutationgaussian, 1, 1};
#default_options.OutputFcns = [];
#default_options.ParetoFraction = 0.35;
#default_options.PenaltyFactor = 100;
#default_options.PlotFcns = [];
#default_options.PlotInterval = 1;
default_options.PopInitRange = [0; 1];
default_options.PopulationSize = 20;
#default_options.PopulationType = "doubleVector";
default_options.SelectionFcn = @selectionstochunif;
#default_options.StallGenLimit = 50;
#default_options.StallTimeLimit = Inf;
default_options.TimeLimit = Inf;
#default_options.TolCon = 1e-6;
#default_options.TolFun = 1e-6;
default_options.UseParallel = "never";
default_options.Vectorized = "off";
endfunction ga/inst/crossoverscattered.m 000644 000767 000000 00000003220 11737424747 017642 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008, 2009, 2011 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 7.0
function xoverKids = crossoverscattered (parents, options, nvars, FitnessFcn,
unused,
thisPopulation)
## simplified example (nvars == 4)
## p1 = [varA varB varC varD]
## p2 = [var1 var2 var3 var4]
## b = [1 1 0 1]
## child = [varA varB var3 varD]
nc_parents = columns (parents);
n_children = nc_parents / 2;
p1(1:n_children, 1:nvars) = \
thisPopulation(parents(1, 1:n_children), 1:nvars);
p2(1:n_children, 1:nvars) = \
thisPopulation(parents(1, n_children + (1:n_children)), 1:nvars);
b(1:n_children, 1:nvars) = randi (1, n_children, nvars); ## TODO: test randi
xoverKids(1:n_children, 1:nvars) = \
b .* p1 + (ones (n_children, nvars) - b) .* p2;
endfunction
## number of input arguments
# TODO
## number of output arguments
# TODO
## type of arguments
# TODO
# TODO
ga/inst/fitscalingrank.m 000644 000767 000000 00000003564 11737424747 016730 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008, 2009 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 1.3.3
function expectation = fitscalingrank (scores, nParents)
nr_scores = rows (scores);
r(1, 1:nr_scores) = ranks (scores(1:nr_scores, 1));
#TODO
#ranks ([7,2,2]) == [3.0,1.5,1.5]
#is [3,1,2] (or [3,2,1]) useful?
expectation_wo_nParents(1, 1:nr_scores) = arrayfun (@(n) 1 / sqrt (n), r);
expectation(1, 1:nr_scores) = \
(nParents / sum (expectation_wo_nParents)) * \
expectation_wo_nParents;
endfunction
## number of input arguments
# TODO
## number of output arguments
# TODO
## type of arguments
# TODO
# TODO
%!shared scores, nParents, expectation
%! scores = rand (20, 1);
%! nParents = 32;
%! expectation = fitscalingrank (scores, nParents);
%!assert (sum (expectation), nParents, 1e-9);
%!test
%! [trash index_min_scores] = min (scores);
%! [trash index_max_expectation] = max (expectation);
%! assert (index_min_scores, index_max_expectation);
%!test
%! [trash index_max_scores] = max (scores);
%! [trash index_min_expectation] = min (expectation);
%! assert (index_max_scores, index_min_expectation); ga/inst/ga.m 000644 000767 000000 00000035521 11737424747 014316 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008, 2010, 2012 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## -*- texinfo -*-
## @deftypefn{Function File} {@var{x} =} ga (@var{fitnessfcn}, @var{nvars})
## @deftypefnx{Function File} {@var{x} =} ga (@var{fitnessfcn}, @var{nvars}, @var{A}, @var{b})
## @deftypefnx{Function File} {@var{x} =} ga (@var{fitnessfcn}, @var{nvars}, @var{A}, @var{b}, @var{Aeq}, @var{beq})
## @deftypefnx{Function File} {@var{x} =} ga (@var{fitnessfcn}, @var{nvars}, @var{A}, @var{b}, @var{Aeq}, @var{beq}, @var{LB}, @var{UB})
## @deftypefnx{Function File} {@var{x} =} ga (@var{fitnessfcn}, @var{nvars}, @var{A}, @var{b}, @var{Aeq}, @var{beq}, @var{LB}, @var{UB}, @var{nonlcon})
## @deftypefnx{Function File} {@var{x} =} ga (@var{fitnessfcn}, @var{nvars}, @var{A}, @var{b}, @var{Aeq}, @var{beq}, @var{LB}, @var{UB}, @var{nonlcon}, @var{options})
## @deftypefnx{Function File} {@var{x} =} ga (@var{problem})
## @deftypefnx{Function File} {[@var{x}, @var{fval}] =} ga (@dots{})
## @deftypefnx{Function File} {[@var{x}, @var{fval}, @var{exitflag}] =} ga (@dots{})
## @deftypefnx{Function File} {[@var{x}, @var{fval}, @var{exitflag}, @var{output}] =} ga (@dots{})
## @deftypefnx{Function File} {[@var{x}, @var{fval}, @var{exitflag}, @var{output}, @var{population}] =} ga (@dots{})
## @deftypefnx{Function File} {[@var{x}, @var{fval}, @var{exitflag}, @var{output}, @var{population}, @var{scores}] =} ga (@dots{})
## Find minimum of function using genetic algorithm.
##
## @strong{Inputs}
## @table @var
## @item fitnessfcn
## The objective function to minimize. It accepts a vector @var{x} of
## size 1-by-@var{nvars}, and returns a scalar evaluated at @var{x}.
## @item nvars
## The dimension (number of design variables) of @var{fitnessfcn}.
## @item options
## The structure of the optimization parameters; can be created using
## the @code{gaoptimset} function. If not specified, @code{ga} minimizes
## with the default optimization parameters.
## @item problem
## A structure containing the following fields:
## @itemize @bullet
## @item @code{fitnessfcn}
## @item @code{nvars}
## @item @code{Aineq}
## @item @code{Bineq}
## @item @code{Aeq}
## @item @code{Beq}
## @item @code{lb}
## @item @code{ub}
## @item @code{nonlcon}
## @item @code{randstate}
## @item @code{randnstate}
## @item @code{solver}
## @item @code{options}
## @end itemize
## @end table
##
## @strong{Outputs}
## @table @var
## @item x
## The local unconstrained found minimum to the objective function,
## @var{fitnessfcn}.
## @item fval
## The value of the fitness function at @var{x}.
## @end table
##
## @seealso{gaoptimset}
## @end deftypefn
## Author: Luca Favatella
## Version: 6.0.1
function [x fval exitflag output population scores] = \
ga (fitnessfcn_or_problem,
nvars,
A = [], b = [],
Aeq = [], beq = [],
LB = [], UB = [],
nonlcon = [],
options = gaoptimset ())
if ((nargout > 6) ||
(nargin < 1) ||
(nargin == 3) ||
(nargin == 5) ||
(nargin == 7) ||
(nargin > 10))
print_usage ();
else
## retrieve the problem structure
if (nargin == 1)
problem = fitnessfcn_or_problem;
else
problem.fitnessfcn = fitnessfcn_or_problem;
problem.nvars = nvars;
problem.Aineq = A;
problem.Bineq = b;
problem.Aeq = Aeq;
problem.Beq = beq;
problem.lb = LB;
problem.ub = UB;
problem.nonlcon = nonlcon;
problem.randstate = rand ("state");
problem.randnstate = randn ("state");
problem.solver = "ga";
problem.options = options;
endif
## call the function that manages the problem structure
[x fval exitflag output population scores] = __ga_problem__ (problem);
endif
endfunction
## number of input arguments
%!shared f, nvars
%! f = @rastriginsfcn;
%! nvars = 2;
%!error x = ga ()
%!error x = ga (f)
%!error x = ga (f, nvars, [])
%!error x = ga (f, nvars, [], [], [])
%!error x = ga (f, nvars, [], [], [], [], [])
%!error x = ga (f, nvars, [], [], [], [], [], [], @(x) [[], []], gaoptimset (), [])
## number of output arguments
# TODO
## type of arguments
%!function f = ff (nvars)
%! f = @(x) sum (x(:, 1:nvars) .** 2, 2);
%!error x = ga (ff (3), 2);
# TODO
# TODO: test that each field in the user-specified "problem" structure is checked
## flawless execution with right arguments
%!shared f, nvars
%! f = @rastriginsfcn;
%! nvars = 2;
%!function [C, Ceq] = nonlcon (x)
%! C = [];
%! Ceq = [];
%!test x = ga (f, nvars);
%!test x = ga (f, nvars, [], []);
%!test x = ga (f, nvars, ones (3, nvars), ones (3, 1));
%!test x = ga (f, nvars, [], [], [], []);
%!test x = ga (f, nvars, [], [], ones (4, nvars), ones (4, 1));
%!test x = ga (f, nvars, [], [], [], [], [], []);
%!test x = ga (f, nvars, [], [], [], [], - Inf (1, nvars), Inf (1, nvars));
%!test x = ga (f, nvars, [], [], [], [], - ones (1, nvars), ones (1, nvars));
%!test x = ga (f, nvars, [], [], [], [], [], [], @(x) [[], []]);
%!test x = ga (f, nvars, [], [], [], [], [], [], @nonlcon);
%!test x = ga (f, nvars, [], [], [], [], [], [], @(x) [[], []], gaoptimset ());
%!test # TODO: convert to error after implementing private ga-specific createOptimProblem. All fields in the user-specified structure should be checked
%! problem = struct ("fitnessfcn", @rastriginsfcn,
%! "nvars", 2,
%! "options", gaoptimset ());
%! x = ga (problem);
## flawless execution with any nvars
%!function f = ff (nvars)
%! f = @(x) sum (x(:, 1:nvars) .** 2, 2);
%!test
%! nvars = 1;
%! x = ga (ff (nvars), nvars);
%!test
%! nvars = 2;
%! x = ga (ff (nvars), nvars);
%!test
%! nvars = 3;
%! x = ga (ff (nvars), nvars);
## flawless execution with any supported optimization parameter
## different from the default value
%!shared f, nvars, default_options
%! f = @rastriginsfcn;
%! nvars = 2;
%! default_options = gaoptimset ();
%!function [C, Ceq] = nonlcon (x)
%! C = [];
%! Ceq = [];
%!test
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, default_options);
%!test # TODO: use non-default value
%! options = gaoptimset ("CreationFcn", @gacreationuniform);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test # TODO: use non-default value
%! options = gaoptimset ("CrossoverFcn", @crossoverscattered);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test
%! options = gaoptimset ("CrossoverFraction", rand);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test
%! ps = getfield (default_options, "PopulationSize");
%! options = gaoptimset ("EliteCount", randi ([0, ps]));
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test
%! options = gaoptimset ("FitnessLimit", 1e-7);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test # TODO: use non-default value
%! options = gaoptimset ("FitnessScalingFcn", @fitscalingrank);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test
%! g = getfield (default_options, "Generations");
%! options = gaoptimset ("Generations", g + 1);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test
%! ps = getfield (default_options, "PopulationSize");
%! ## Initial population can be partial
%! options_w_full_ip = \
%! gaoptimset ("InitialPopulation", rand (ps, nvars));
%! partial_ip = randi ([0, ps - 1]);
%! options_w_partial_ip = \
%! gaoptimset ("InitialPopulation", rand (partial_ip, nvars));
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options_w_full_ip);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options_w_partial_ip);
%!test
%! ps = getfield (default_options, "PopulationSize");
%! ## Initial scores needs initial population
%!
%! options_w_full_ip_full_is = \
%! gaoptimset ("InitialPopulation", rand (ps, nvars),
%! "InitialScores", rand (ps, 1 ));
%! partial_ip = randi ([2, ps - 1]);
%! options_w_partial_ip_full_is = \
%! gaoptimset ("InitialPopulation", rand (partial_ip, nvars),
%! "InitialScores", rand (partial_ip, 1 ));
%!
%! ## Initial scores can be partial
%! partial_is_when_full_ip = randi ([1, ps - 1]);
%! partial_is_when_partial_ip = randi ([1, partial_ip - 1]);
%! options_w_full_ip_partial_is = \
%! gaoptimset ("InitialPopulation", rand (ps, nvars),
%! "InitialScores", rand (partial_is_when_full_ip, 1 ));
%! options_w_partial_ip_partial_is = \
%! gaoptimset ("InitialPopulation", rand (partial_ip, nvars),
%! "InitialScores", rand (partial_is_when_partial_ip, 1 ));
%!
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon,
%! options_w_full_ip_full_is);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon,
%! options_w_partial_ip_full_is);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon,
%! options_w_full_ip_partial_is);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon,
%! options_w_partial_ip_partial_is);
%!test # TODO: use non-default value
%! options = gaoptimset ("MutationFcn", {@mutationgaussian, 1, 1});
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test
%! options = gaoptimset ("PopInitRange", [-2; 2]);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test
%! options = gaoptimset ("PopulationSize", 200);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test # TODO: use non-default value
%! options = gaoptimset ("SelectionFcn", @selectionstochunif);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test # TODO: use non-default value
%! options = gaoptimset ("TimeLimit", Inf);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!error # TODO: this should become test
%! options = gaoptimset ("UseParallel", "always");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test
%! options = gaoptimset ("Vectorized", "on");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
## error with conflicting optimization parameters: population size et al.
%!shared f, nvars
%! f = @rastriginsfcn;
%! nvars = 2;
%!function [C, Ceq] = nonlcon (x)
%! C = [];
%! Ceq = [];
%!error # Elite count cannot be greater than the population size
%! ps = 3;
%! bad_options = gaoptimset ("PopulationSize", ps,
%! "EliteCount", ps + 1);
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, bad_options);
%!error # The number of individuals in the initial population cannot be greater of the population size
%! ps = 3;
%! bad_options = gaoptimset ("PopulationSize", ps,
%! "InitialPopulation", zeros (ps + 1, nvars));
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, bad_options);
%!error # Initial scores cannot be specified without specifying the initial population too
%! bad_options = gaoptimset ("InitialScores", zeros (3, 1));
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, bad_options);
%!error # The number of initial scores specified cannot be greater of the number of individuals in the initial population
%! ip = 3;
%! bad_options = gaoptimset ("InitialPopulation", zeros (ip, nvars),
%! "InitialScores", zeros (ip + 1, 1));
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, bad_options);
## error with vectorized evaluation of objective function. Vectorized
## objective functions are better because can be evaluated both as
## serial and vectorized.
%!shared nvars
%! nvars = 2;
%!function [C, Ceq] = nonlcon (x)
%! C = [];
%! Ceq = [];
%!function f = ff (nvars)
%! f = @(x) sum (x(:, 1:nvars) .** 2, 2);
%!function f_not_vectorized = ff_not_vectorized (nvars)
%! f_not_vectorized = @(x) sum (x(1:nvars) .** 2);
%!test # A non-vectorized objective function works when no vectorization is required
%! f = ff_not_vectorized (nvars);
%! options = gaoptimset ("Vectorized", "off");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!error # A non-vectorized objective function does not work when vectorization is required
%! f = ff_not_vectorized (nvars);
%! options = gaoptimset ("Vectorized", "on");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test # A vectorized objective function works when no vectorization is required
%! f = ff (nvars);
%! options = gaoptimset ("Vectorized", "off");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!test # A vectorized objective function works when vectorization is required
%! f = ff (nvars);
%! options = gaoptimset ("Vectorized", "on");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
## error with conflicting optimization parameters: parallel and
## vectorized evaluation of objective function
%!shared f, nvars
%! f = @rastriginsfcn;
%! nvars = 2;
%!function [C, Ceq] = nonlcon (x)
%! C = [];
%! Ceq = [];
%!test
%! options = gaoptimset ("UseParallel", "never",
%! "Vectorized", "off");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!error # TODO: this should become test
%! options = gaoptimset ("UseParallel", "always",
%! "Vectorized", "off");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!error
%! bad_options = gaoptimset ("UseParallel", "garbage",
%! "Vectorized", "off");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, bad_options);
%!test
%! options = gaoptimset ("UseParallel", "never",
%! "Vectorized", "on");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, options);
%!warning
%! bad_options = gaoptimset ("UseParallel", "always",
%! "Vectorized", "on");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, bad_options);
%!warning
%! bad_options = gaoptimset ("UseParallel", "garbage",
%! "Vectorized", "on");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, bad_options);
%!error
%! bad_options = gaoptimset ("UseParallel", "never",
%! "Vectorized", "garbage");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, bad_options);
%!error
%! bad_options = gaoptimset ("UseParallel", "always",
%! "Vectorized", "garbage");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, bad_options);
%!error
%! bad_options = gaoptimset ("UseParallel", "garbage",
%! "Vectorized", "garbage");
%! x = ga (f, nvars, [], [], [], [], [], [], @nonlcon, bad_options);
ga/inst/gacreationuniform.m 000644 000767 000000 00000003726 11737424747 017445 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## -*- texinfo -*-
## @deftypefn{Function File} {@var{Population} =} gacreationuniform (@var{GenomeLength}, @var{FitnessFcn}, @var{options})
## Create a random initial population with a uniform distribution.
##
## @strong{Inputs}
## @table @var
## @item GenomeLength
## The number of indipendent variables for the fitness function.
## @item FitnessFcn
## The fitness function.
## @item options
## The options structure.
## @end table
##
## @strong{Outputs}
## @table @var
## @item Population
## The initial population for the genetic algorithm.
## @end table
##
## @seealso{ga, gaoptimset}
## @end deftypefn
## Author: Luca Favatella
## Version: 4.9
function Population = gacreationuniform (GenomeLength, FitnessFcn, options)
[LB(1, 1:GenomeLength) UB(1, 1:GenomeLength)] = \
__ga_popinitrange__ (options.PopInitRange, GenomeLength);
## pseudocode
##
## Population = Delta * RandomPopulationBetween0And1 + Offset
Population(1:options.PopulationSize, 1:GenomeLength) = \
((ones (options.PopulationSize, 1) * (UB - LB)) .* \
rand (options.PopulationSize, GenomeLength)) + \
(ones (options.PopulationSize, 1) * LB);
endfunction
## number of input arguments
# TODO
## number of output arguments
# TODO
## type of arguments
# TODO
# TODO
ga/inst/gaoptimset.m 000644 000767 000000 00000007737 11737424747 016113 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008, 2009, 2010 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## -*- texinfo -*-
## @deftypefn{Function File} {@var{options} =} gaoptimset
## @deftypefnx{Function File} {@var{options} =} gaoptimset ('@var{param1}', @var{value1}, '@var{param2}', @var{value2}, @dots{})
## Create genetic algorithm options structure.
##
## @strong{Inputs}
## @table @var
## @item param
## Parameter to set. Unspecified parameters are set to their default
## values; specifying no parameters is allowed.
## @item value
## Value of @var{param}.
## @end table
##
## @strong{Outputs}
## @table @var
## @item options
## Structure containing the options, or parameters, for the genetic algorithm.
## @end table
##
## @strong{Options}
## @table @code
## @item CreationFcn
## @item CrossoverFcn
## @item CrossoverFraction
## @item EliteCount
## @item FitnessLimit
## @item FitnessScalingFcn
## @item Generations
## @item InitialPopulation
## Can be partial.
## @item InitialScores
## column vector | [] (default) . Can be partial.
## @item MutationFcn
## @item PopInitRange
## @item PopulationSize
## @item SelectionFcn
## @item TimeLimit
## @item UseParallel
## "always" | "never" (default) . Parallel evaluation of objective function. TODO: parallel evaluation of nonlinear constraints
## @item Vectorized
## "on" | "off" (default) . Vectorized evaluation of objective function. TODO: vectorized evaluation of nonlinear constraints
## @end table
##
## @seealso{ga}
## @end deftypefn
## Author: Luca Favatella
## Version: 4.4.7
function options = gaoptimset (varargin)
if ((nargout != 1) ||
(mod (length (varargin), 2) == 1))
print_usage ();
else
## initialize the return variable to a structure with all parameters
## set to their default value
options = __gaoptimset_default_options__ ();
## set custom options
for i = 1:2:length (varargin)
param = varargin{i};
value = varargin{i + 1};
if (! isfield (options, param))
error ("wrong parameter");
else
options = setfield (options, param, value);
endif
endfor
endif
endfunction
## number of input arguments
%!error options = gaoptimset ("odd number of arguments")
%!error options = gaoptimset ("Generations", 123, "odd number of arguments")
## number of output arguments
%!error gaoptimset ("Generations", 123)
%!error [a, b] = gaoptimset ("Generations", 123)
## type of arguments
# TODO
%!#error options = gaoptimset ("Vectorized", "bad value") # TODO: fix
%!#error options = gaoptimset ("UseParallel", "bad value") # TODO: fix
# TODO: structure/add tests below
%!assert (getfield (gaoptimset ("Generations", 123), "Generations"), 123)
%!test
%! options = gaoptimset ("EliteCount", 1,
%! "FitnessLimit", 1e-7,
%! "Generations", 1000,
%! "PopInitRange", [-5; 5],
%! "PopulationSize", 200);
%!
%! ## "CrossoverFraction" is not specified, so gaoptimset should put the default value: testing this too
%! assert ([(getfield (options, "CrossoverFraction"));
%! (getfield (options, "EliteCount"));
%! (getfield (options, "FitnessLimit"));
%! (getfield (options, "Generations"));
%! (getfield (options, "PopInitRange"));
%! (getfield (options, "PopulationSize"))],
%! [0.8; 1; 1e-7; 1000; [-5; 5]; 200])
ga/inst/mutationgaussian.m 000644 000767 000000 00000003741 11737424747 017321 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 1.7.1
function mutationChildren = \
mutationgaussian (parents, options, nvars, FitnessFcn,
state, thisScore,
thisPopulation)
[LB(1, 1:nvars) UB(1, 1:nvars)] = \
__ga_popinitrange__ (options.PopInitRange, nvars);
## start mutationgaussian logic
Scale = options.MutationFcn{1, 2};
#assert (size (Scale), [1 1]); ## DEBUG
Shrink = options.MutationFcn{1, 3};
#assert (size (Shrink), [1 1]); ## DEBUG
## initial standard deviation (i.e. when state.Generation == 0)
tmp_std = Scale * (UB - LB); ## vector = scalar * vector
## recursively compute current standard deviation
for k = 1:state.Generation
tmp_std(1, 1:nvars) = (1 - Shrink * (k / options.Generations)) * tmp_std;
endfor
current_std(1, 1:nvars) = tmp_std;
nc_parents = columns (parents);
expanded_current_std(1:nc_parents, 1:nvars) = \
ones (nc_parents, 1) * current_std;
## finally add random numbers
mutationChildren(1:nc_parents, 1:nvars) = \
thisPopulation(parents(1, 1:nc_parents), 1:nvars) + \
expanded_current_std .* randn (nc_parents, nvars);
endfunction
## number of input arguments
# TODO
## number of output arguments
# TODO
## type of arguments
# TODO
# TODO
ga/inst/rastriginsfcn.m 000644 000767 000000 00000003243 11737424747 016577 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008, 2009, 2010, 2012 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## -*- texinfo -*-
## @deftypefn{Function File} {@var{y} =} rastriginsfcn (@var{x})
## Rastrigin's function.
## @end deftypefn
## Author: Luca Favatella
## Version: 2.0
function retval = rastriginsfcn (x)
if ((nargout != 1) ||
(nargin != 1) || (columns (x) != 2))
print_usage ();
else
x1 = x(:, 1);
x2 = x(:, 2);
retval = 20 + (x1 .** 2) + (x2 .** 2) - 10 .* (cos (2 .* pi .* x1) +
cos (2 .* pi .* x2));
endif
endfunction
## number of input arguments
%!error y = rastriginsfcn ()
%!error y = rastriginsfcn ([0, 0], "other argument")
## number of output arguments
%!error [y1, y2] = rastriginsfcn ([0, 0])
## type of arguments
%!error y = rastriginsfcn ([0; 0])
%!error y = rastriginsfcn (zeros (2, 3)) # TODO: document size of x
%!assert (rastriginsfcn ([0, 0]), 0)
%!assert (rastriginsfcn ([0, 0; 0, 0]), [0; 0])
%!assert (rastriginsfcn (zeros (3, 2)), [0; 0; 0])
ga/inst/selectionstochunif.m 000644 000767 000000 00000003122 11737424747 017627 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2008 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## Author: Luca Favatella
## Version: 1.3
function parents = selectionstochunif (expectation, nParents, options)
nc_expectation = columns (expectation);
line(1, 1:nc_expectation) = cumsum (expectation(1, 1:nc_expectation));
max_step_size = line(1, nc_expectation);
step_size = max_step_size * rand ();
steps(1, 1:nParents) = rem (step_size * (1:nParents), max_step_size);
for index_steps = 1:nParents ## fix an entry of the steps (or parents) vector
#assert (steps(1, index_steps) < max_step_size); ## DEBUG
index_line = 1;
while (steps(1, index_steps) >= line(1, index_line))
#assert ((index_line >= 1) && (index_line < nc_expectation)); ## DEBUG
index_line++;
endwhile
parents(1, index_steps) = index_line;
endfor
endfunction
## number of input arguments
# TODO
## number of output arguments
# TODO
## type of arguments
# TODO
# TODO
ga/inst/test_ga.m 000644 000767 000000 00000002400 11737424747 015343 0 ustar 00slackydeb wheel 000000 000000 ## Copyright (C) 2012 Luca Favatella
##
## This program is free software; you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation; either version 2 of the License, or
## (at your option) any later version.
##
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with this program; If not, see .
## -*- texinfo -*-
## @deftypefn{Script File} {} test_ga
## Execute all available tests at once.
## @end deftypefn
## Author: Luca Favatella
## Created: March 2012
## Version: 0.3
## Creation
test gacreationuniform
## Fitness Scaling
test fitscalingrank
## Selection
test selectionstochunif
## Crossover
test crossoverscattered
## Mutation
test mutationgaussian
## Utility
test rastriginsfcn
## Genetic Algorithm
test gaoptimset
test ga
## Private functions
test __ga_initial_population__
test __ga_problem_update_state_at_each_generation__
ga/doc/README 000644 000767 000000 00000000461 11737424747 014214 0 ustar 00slackydeb wheel 000000 000000 STATUS (BY EXAMPLES)
See tests of the ga function.
TODO
create a demo
write a proper README
linear constraints (needs mutationadaptfeasible and perhaps LMI)
nonlinear constraints
subpopulations and migrations
bitstring support
plot functions
more texinfo
handle TODOs in the code
integer constraints
ga/DESCRIPTION 0000644 0001750 0001750 00000000464 11737651143 015467 0 ustar 00carandraug carandraug 0000000 0000000 Name: ga
Version: 0.10.0
Date: 2012-04-06
Author: Luca Favatella
Maintainer: Luca Favatella
Title: Genetic Algorithm
Description: Genetic optimization code
Categories: Optimization
Depends: octave (>= 3.4.0)
Autoload: yes
License: GPLv2+
Url: http://octave.sf.net