ga-0.10.4/ 0000755 0000000 0000000 00000000000 14616472453 007125 5 ustar 00 ga-0.10.4/COPYING 0000644 0000000 0000000 00000104513 14616472453 010164 0 ustar 00 GNU GENERAL PUBLIC LICENSE
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How to Apply These Terms to Your New Programs
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Also add information on how to contact you by electronic and paper mail.
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For more information on this, and how to apply and follow the GNU GPL, see
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The GNU General Public License does not permit incorporating your program
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Public License instead of this License. But first, please read
.
ga-0.10.4/DESCRIPTION 0000644 0000000 0000000 00000000517 14616472453 010636 0 ustar 00 Name: ga
Version: 0.10.4
Date: 2024-05-07
Author: Luca Favatella
Maintainer: Octave-Forge community
Title: Genetic Algorithm
Description: Genetic optimization code
Categories: Optimization
Depends: octave (>= 4.0.0)
Autoload: yes
License: GPL version 3 or later
Url: http://octave.sf.net
ga-0.10.4/INDEX 0000644 0000000 0000000 00000000402 14616472453 007713 0 ustar 00 ga >> Genetic Algorithm
Genetic Algorithm
ga
gaoptimset
Creation
gacreationuniform
Fitness Scaling
fitscalingrank
Selection
selectionstochunif
Crossover
crossoverscattered
Mutation
mutationgaussian
Utility
rastriginsfcn
Miscellaneous
test_ga
ga-0.10.4/Makefile 0000644 0000000 0000000 00000022547 14616472453 010577 0 ustar 00 ## Copyright 2015-2016 Carnë Draug
## Copyright 2015-2016 Oliver Heimlich
## Copyright 2017 Julien Bect
## Copyright 2017 Olaf Till
## Copyright 2019 John Donoghue
##
## Copying and distribution of this file, with or without modification,
## are permitted in any medium without royalty provided the copyright
## notice and this notice are preserved. This file is offered as-is,
## without any warranty.
## Some basic tools (can be overriden using environment variables)
SED ?= sed
TAR ?= tar
GREP ?= grep
CUT ?= cut
TR ?= tr
## Note the use of ':=' (immediate set) and not just '=' (lazy set).
## http://stackoverflow.com/a/448939/1609556
package := $(shell $(GREP) "^Name: " DESCRIPTION | $(CUT) -f2 -d" " | \
$(TR) '[:upper:]' '[:lower:]')
version := $(shell $(GREP) "^Version: " DESCRIPTION | $(CUT) -f2 -d" ")
## These are the paths that will be created for the releases.
target_dir := target
release_dir := $(target_dir)/$(package)-$(version)
release_tarball := $(target_dir)/$(package)-$(version).tar.gz
html_dir := $(target_dir)/$(package)-html
html_tarball := $(target_dir)/$(package)-html.tar.gz
## Using $(realpath ...) avoids problems with symlinks due to bug
## #50994 in Octaves scripts/pkg/private/install.m. But at least the
## release directory above is needed in the relative form, for 'git
## archive --format=tar --prefix=$(release_dir).
real_target_dir := $(realpath .)/$(target_dir)
installation_dir := $(real_target_dir)/.installation
package_list := $(installation_dir)/.octave_packages
install_stamp := $(installation_dir)/.install_stamp
## These can be set by environment variables which allow to easily
## test with different Octave versions.
ifndef OCTAVE
OCTAVE := octave
endif
OCTAVE := $(OCTAVE) --no-gui --silent --norc
MKOCTFILE ?= mkoctfile
## Command used to set permissions before creating tarballs
FIX_PERMISSIONS ?= chmod -R a+rX,u+w,go-w,ug-s
## Detect which VCS is used
vcs := $(if $(wildcard .hg),hg,$(if $(wildcard .git),git,unknown))
ifeq ($(vcs),hg)
release_dir_dep := .hg/dirstate
HG := hg
HG_CMD = $(HG) --config alias.$(1)=$(1) --config defaults.$(1)= $(1)
HG_ID := $(shell $(call HG_CMD,identify) --id | sed -e 's/+//' )
REPO_TIMESTAMP := $(firstword $(shell $(call HG_CMD,log) --rev $(HG_ID) --template '{date|hgdate}'))
endif
ifeq ($(vcs),git)
release_dir_dep := .git/index
GIT := git
REPO_TIMESTAMP := $(firstword $(shell $(GIT) log -n1 --date=unix --format="%ad"))
endif
TAR_REPRODUCIBLE_OPTIONS := --sort=name --mtime="@$(REPO_TIMESTAMP)" --owner=0 --group=0 --numeric-owner
TAR_OPTIONS := --format=ustar $(TAR_REPRODUCIBLE_OPTIONS)
## .PHONY indicates targets that are not filenames
## (https://www.gnu.org/software/make/manual/html_node/Phony-Targets.html)
.PHONY: help
## make will display the command before runnning them. Use @command
## to not display it (makes specially sense for echo).
help:
@echo "Targets:"
@echo " dist - Create $(release_tarball) for release."
@echo " html - Create $(html_tarball) for release."
@echo " release - Create both of the above and show md5sums."
@echo " install - Install the package in $(installation_dir), where it is not visible in a normal Octave session."
@echo " check - Execute package tests."
@echo " doctest - Test the help texts with the doctest package."
@echo " run - Run Octave with the package installed in $(installation_dir) in the path."
@echo " clean - Remove everything made with this Makefile."
##
## Recipes for release tarballs (package + html)
##
.PHONY: release dist html clean-tarballs clean-unpacked-release
## To make a release, build the distribution and html tarballs.
release: dist html
md5sum $(release_tarball) $(html_tarball)
@echo "Upload @ https://sourceforge.net/p/octave/package-releases/new/"
@echo " and note the changeset the release corresponds to"
## dist and html targets are only PHONY/alias targets to the release
## and html tarballs.
dist: $(release_tarball)
html: $(html_tarball)
## An implicit rule with a recipe to build the tarballs correctly.
%.tar.gz: %
$(TAR) -cf - $(TAR_OPTIONS) -C "$(target_dir)/" "$(notdir $<)" | gzip -9n > "$@"
clean-tarballs:
@echo "## Cleaning release tarballs (package + html)..."
-$(RM) $(release_tarball) $(html_tarball)
@echo
## Create the unpacked package.
##
## Notes:
## * having ".hg/dirstate" (or ".git/index") as a prerequesite means it is
## only rebuilt if we are at a different commit.
## * the variable RM usually defaults to "rm -f"
## * having this recipe separate from the one that makes the tarball
## makes it easy to have packages in alternative formats (such as zip)
## * note that if a commands needs to be run in a specific directory,
## the command to "cd" needs to be on the same line. Each line restores
## the original working directory.
$(release_dir): $(release_dir_dep)
-$(RM) -r "$@"
ifeq (${vcs},hg)
hg archive --exclude ".hg*" --type files "$@"
endif
ifeq (${vcs},git)
git archive --format=tar --prefix="$@/" HEAD | $(TAR) -x
$(RM) "$@/.gitignore"
endif
## Don't fall back to run the supposed necessary contents of
## 'bootstrap' here. Users are better off if they provide
## 'bootstrap'. Administrators, checking build reproducibility, can
## put in the missing 'bootstrap' file if they feel they know its
## necessary contents.
ifneq (,$(wildcard src/bootstrap))
cd "$@/src" && ./bootstrap && $(RM) -r "autom4te.cache"
endif
## Uncomment this if your src/Makefile.in has these targets for
## pre-building something for the release (e.g. documentation).
# cd "$@/src" && ./configure && $(MAKE) prebuild && \
# $(MAKE) distclean && $(RM) Makefile
##
${FIX_PERMISSIONS} "$@"
run_in_place = $(OCTAVE) --eval ' pkg ("local_list", "$(package_list)"); ' \
--eval ' pkg ("load", "$(package)"); '
# html_options = --eval 'options = get_html_options ("octave-forge");'
## Uncomment this for package documentation.
##html_options = --eval 'options = get_html_options ("octave-forge");' \
## --eval 'options.package_doc = "$(package).texi";'
html_options = --eval 'options = get_html_options ("octave-forge");'
$(html_dir): $(install_stamp)
$(RM) -r "$@";
$(run_in_place) \
--eval ' pkg load generate_html; ' \
$(html_options) \
--eval ' generate_package_html ("$(package)", "$@", options); ';
$(FIX_PERMISSIONS) "$@";
clean-unpacked-release:
@echo "## Cleaning unpacked release tarballs (package + html)..."
-$(RM) -r $(release_dir) $(html_dir)
@echo
##
## Recipes for installing the package.
##
.PHONY: install clean-install
octave_install_commands = \
' llist_path = pkg ("local_list"); \
mkdir ("$(installation_dir)"); \
load (llist_path); \
local_packages(cellfun (@ (x) strcmp ("$(package)", x.name), local_packages)) = []; \
save ("$(package_list)", "local_packages"); \
pkg ("local_list", "$(package_list)"); \
pkg ("prefix", "$(installation_dir)", "$(installation_dir)"); \
pkg ("install", "-local", "-verbose", "$(release_tarball)"); '
## Install unconditionally. Maybe useful for testing installation with
## different versions of Octave.
install: $(release_tarball)
@echo "Installing package under $(installation_dir) ..."
$(OCTAVE) --eval $(octave_install_commands)
touch $(install_stamp)
## Install only if installation (under target/...) is not current.
$(install_stamp): $(release_tarball)
@echo "Installing package under $(installation_dir) ..."
$(OCTAVE) --eval $(octave_install_commands)
touch $(install_stamp)
clean-install:
@echo "## Cleaning installation under $(installation_dir) ..."
-$(RM) -r $(installation_dir)
@echo
##
## Recipes for testing purposes
##
.PHONY: run doctest check
## Start an Octave session with the package directories on the path for
## interactice test of development sources.
run: $(install_stamp)
$(run_in_place) --persist
rungui: $(install_stamp)
$(run_in_place) --persist --gui
## Test example blocks in the documentation. Needs doctest package
## https://octave.sourceforge.io/doctest/index.html
doctest: $(install_stamp)
$(run_in_place) --eval 'pkg load doctest;' \
--eval "targets = '$(shell (ls inst; ls src | $(GREP) .oct) | $(CUT) -f2 -d@ | $(CUT) -f1 -d.)';" \
--eval "targets = strsplit (targets, ' '); doctest (targets);"
## Test package.
octave_test_commands = \
' pkgs = pkg("list", "$(package)"); \
cd ("$(target_dir)/"); \
dirs = {sprintf(".installation/%s-%s", pkgs{1}.name, pkgs{1}.version)}; \
__run_test_suite__ (dirs, {}); '
octave_test_commands = \
' pkgs = pkg("list", "$(package)"); \
dirs = {pkgs{1}.dir}; \
__run_test_suite__ (dirs, {}); '
## the following works, too, but provides no overall summary output as
## __run_test_suite__ does:
##
## else cellfun (@runtests, horzcat (cellfun (@ (dir) ostrsplit (([~, dirs] = system (sprintf ("find %s -type d", dir))), "\n\r", true), dirs, "UniformOutput", false){:})); endif '
check: $(install_stamp)
$(run_in_place) --eval $(octave_test_commands)
clean-check:
@echo "## Removing fntests.log..."
-$(RM) $(target_dir)/fntests.log
@echo
##
## CLEAN
##
.PHONY: clean
clean: clean-tarballs clean-unpacked-release clean-install clean-check
@echo "## Removing target directory (if empty)..."
-if [ -d $(target_dir) ]; then rmdir $(target_dir); fi
@echo
@echo "## Cleaning done"
@echo
ga-0.10.4/NEWS 0000644 0000000 0000000 00000003752 14616472453 007633 0 ustar 00 Summary of important user-visible changes for releases of the ga package
===============================================================================
ga-0.10.4 Release Date: 2024-05-07 Release Manager: John Donoghue
===============================================================================
** Updates for octave 9 compatibility
===============================================================================
ga-0.10.3 Release Date: 2022-01-14 Release Manager: John Donoghue
===============================================================================
** Updates for octave 7 compatibility
===============================================================================
ga-0.10.2 Release Date: 2020-12-02 Release Manager: John Donoghue
===============================================================================
** Bug fixes #59299
===============================================================================
ga-0.10.1 Release Date: 2019-06-04 Release Manager: John Donoghue
===============================================================================
** Bug fixes #55348, #53875
** minor updates for octave capability
** minor documentation updates
===============================================================================
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-0.10.4/devel/ 0000755 0000000 0000000 00000000000 14616472453 010224 5 ustar 00 ga-0.10.4/devel/INFO 0000644 0000000 0000000 00000000240 14616472453 010676 0 ustar 00 The folder "devel" and its content is ignored by "pkg install". The
folder is intended for draft code and other stuff which is not
suitable for "normal" users.
ga-0.10.4/devel/demo_ga.m 0000644 0000000 0000000 00000012432 14616472453 011777 0 ustar 00 ## Copyright (C) 2012-2019 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 3 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} {} demo_ga
## Run a demo of the genetic algorithm package. The current
## implementation is only a placeholder.
## @end deftypefn
## Author: Luca Favatella
## Created: March 2012
## Version: 0.0.4
demo demo_ga
%!demo
%! % TODO
## This code is a simple example of the usage of ga
# TODO: convert to demo
# %!xtest assert (ga (@rastriginsfcn, 2), [0, 0], 1e-3)
## This code shows that ga optimizes also functions whose minimum is not
## in zero
# TODO: convert to demo
# %!xtest
# %! min = [-1, 2];
# %! assert (ga (struct ("fitnessfcn", @(x) rastriginsfcn (x - min), "nvars", 2, "options", gaoptimset ("FitnessLimit", 1e-7, "Generations", 1000, "PopInitRange", [-5; 5], "PopulationSize", 200))), min, 1e-5)
## This code shows that the "Vectorize" option usually speeds up execution
# TODO: convert to demo
# %!test
# %!
# %! tic ();
# %! ga (struct ("fitnessfcn", @rastriginsfcn, "nvars", 2, "options", gaoptimset ("Generations", 10, "PopulationSize", 200)));
# %! elapsed_time = toc ();
# %!
# %! tic ();
# %! ga (struct ("fitnessfcn", @rastriginsfcn, "nvars", 2, "options", gaoptimset ("Generations", 10, "PopulationSize", 200, "Vectorized", "on")));
# %! elapsed_time_with_vectorized = toc ();
# %!
# %! assert (elapsed_time > elapsed_time_with_vectorized);
## The "UseParallel" option should speed up execution
# TODO: write demo (after implementing
# UseParallel) - low priority
## This code shows a more complex objective function
# TODO: convert to demo
# %!test x = ga (struct ("fitnessfcn", @(x) rastriginsfcn (x(1:2)) + ((x(3) ** 2) - (cos (2 * pi * x(3))) + 1) + (x(4) ** 2), "nvars", 4, "options", gaoptimset ()));
## TODO: these should probably become tests (test, not xtest) using a deterministic sequence of random number
##
## simple optimization result checks. Failures here could happen because
## of non-determinism in the result but if one of these tests always
## fails for you, plese consider dropping an email to the octave-forge
## mailing list .
# %!function f = ff (min)
# %! f = @(x) sum ((x(:, 1:(columns (min))) - repmat (min,
# %! rows (x), 1)) .** 2, 2);
# %!function [C, Ceq] = nonlcon (x)
# %! C = [];
# %! Ceq = [];
# %!function r = rand_porcelain (interval_min, interval_max, nvars)
# %! assert (interval_min < interval_max);
# %! r = interval_min + ((interval_max - interval_min) * rand (1, nvars));
# %!function t = tol (nvars)
# %! t = repelems (0.15, [1; nvars]);
# %!xtest
# %! nvars = 1;
# %! minimum = zeros (1, nvars);
# %! assert (ga (ff (minimum), nvars), minimum, tol (nvars));
# %!xtest
# %! nvars = 2;
# %! minimum = zeros (1, nvars);
# %! assert (ga (ff (minimum), nvars), minimum, tol (nvars));
# %!xtest
# %! nvars = 3;
# %! minimum = zeros (1, nvars);
# %! assert (ga (ff (minimum), nvars), minimum, tol (nvars));
# %!xtest
# %! nvars = 1;
# %! minimum = ones (1, nvars);
# %! assert (ga (ff (minimum), nvars), minimum, tol (nvars));
# %!xtest
# %! nvars = 2;
# %! minimum = ones (1, nvars);
# %! assert (ga (ff (minimum), nvars), minimum, tol (nvars));
# %!xtest
# %! nvars = 3;
# %! minimum = ones (1, nvars);
# %! assert (ga (ff (minimum), nvars), minimum, tol (nvars));
# %!xtest
# %! nvars = 1;
# %! interval_min = -10;
# %! interval_max = 10;
# %! minimum = - rand_porcelain (interval_min, interval_max, nvars);
# %! options = gaoptimset ("PopInitRange", 2 .* [interval_min; interval_max],
# %! "CrossoverFraction", 0.2);
# %! x = ga (ff (minimum), nvars, [], [], [], [], [], [], @nonlcon, options);
# %! assert (x, minimum, 4 .* tol (nvars));
# %!xtest
# %! nvars = 2;
# %! interval_min = -10;
# %! interval_max = 10;
# %! minimum = - rand_porcelain (interval_min, interval_max, nvars);
# %! options = gaoptimset ("PopInitRange", 2 .* [interval_min; interval_max],
# %! "CrossoverFraction", 0.2);
# %! x = ga (ff (minimum), nvars, [], [], [], [], [], [], @nonlcon, options);
# %! assert (x, minimum, 4 .* tol (nvars));
# %!xtest
# %! nvars = 3;
# %! interval_min = -10;
# %! interval_max = 10;
# %! minimum = - rand_porcelain (interval_min, interval_max, nvars);
# %! options = gaoptimset ("PopInitRange", 2 .* [interval_min; interval_max],
# %! "CrossoverFraction", 0.2);
# %! x = ga (ff (minimum), nvars, [], [], [], [], [], [], @nonlcon, options);
# %! assert (x, minimum, 4 .* tol (nvars));
ga-0.10.4/devel/release 0000755 0000000 0000000 00000012121 14616472453 011567 0 ustar 00 #! /bin/sh
## 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 .
## Ease the preparation of Octave-Forge package and function
## reference, automating the steps described at:
## http://octave.sourceforge.net/developers.html
##
## This script:
## - Must be executed from the root directory of the package
## (i.e. where the DESCRIPTION file is placed);
## - Extracts package name and version from the DESCRIPTION file;
## - Extracts code from the current directory (git-svn is assumed at
## the moment, code for svn is disabled ATM) to a sandbox dir;
## - Creates package and function reference in the sandbox dir;
## - Lists created files in the sandbox dir.
##
## Comment/uncomment the relevant lines in the the vcs_export()
## function in order to use svn or hg or git-svn (default).
##
##
## This is an alternative for releasePKG, available at:
## http://octave.svn.sourceforge.net/viewvc/octave/trunk/octave-forge/admin/releasePKG.m?view=log
## Usage of and contribution to releasePKG is recommended.
##
## Reference: http://sourceforge.net/mailarchive/message.php?msg_id=29010854
## Functions
usage() {
echo "Usage: $(basename $0)"
echo "Create Octave-Forge package and function reference"
echo ""
echo "Code is taken from the current dir."
echo "Release files are created in a sandbox dir whose details are printed at the end of the script execution."
}
mktempd() {
TemplateCore=$1
Template="/tmp/${TemplateCore}.XXXXXX"
mktemp -d $Template
}
## John W. Eaton, David Bateman, Søren Hauberg, "GNU Octave - Free
## Your Numbers", Edition 3 for Octave version 3.6.1, February 2011
##
## 37.4.1 The DESCRIPTION File
##
## The ‘DESCRIPTION’ file contains various information about the
## package, such as its name, author, and version. This file has a
## very simple format
## • Lines starting with ‘#’ are comments.
## • Lines starting with a blank character are continuations from the
## • previous line.
## • Everything else is of the form NameOfOption: ValueOfOption.
## The following is a simple example of a ‘DESCRIPTION’ file
## Name: The name of my package
## Version: 1.0.0
## [...]
## The package manager currently recognizes the following keywords
## Name Name of the package.
## Version Version of the package. A package version must be 3
## numbers separated by a dot.
value_of_option() {
DescriptionFile=$1
NameOfOption=$2
grep -v "^[# ]" $DescriptionFile | grep "^${NameOfOption}" | cut -d " " -f 2
}
vcs_export() {
Path=$1
#svn export . $Path ## svn ## svn is untested TODO: test
#hg archive $Path ## hg. Reference: http://sourceforge.net/mailarchive/message.php?msg_id=29008793
git archive master | tar -x -C $Path ## git-svn
}
targz_md5_uue() {
ArchiveFile=$1
File=$2 ## Could also be a dir
tar czf $ArchiveFile $File
md5 $ArchiveFile > ${ArchiveFile}.md5
uuencode $ArchiveFile < $ArchiveFile > ${ArchiveFile}.uue
}
## Main
## References:
## http://octave.sourceforge.net/developers.html
## Assumption: this script is run in the root directory of the
## Octave-Forge to be released
DescriptionFile=$(pwd)/DESCRIPTION
if [ ! -r $DescriptionFile ]; then
usage
exit
fi
## Infer package name
Pkg=$(value_of_option $DescriptionFile "Name")
## Create temporary sandbox dir
TmpDir=$(mktempd $Pkg)
## Create an unversioned copy of the package in the sandbox dir
mkdir ${TmpDir}/${Pkg}
vcs_export ${TmpDir}/${Pkg}
#rm -r ${TmpDir}/${Pkg}/devel ## Do not release the devel/ folder
## Move to sandbox dir
cd $TmpDir
## You have already manually bumped the `Version' number (and
## optionally the `SVNRelease') in the package DESCRIPTION file
##
## Infer package version
Version=$(value_of_option $DescriptionFile "Version")
## produce a tar.gz of the package, take note of its md5 checksum and
## encode it with uuencode
PkgTarGz="${Pkg}-${Version}.tar.gz"
targz_md5_uue $PkgTarGz $Pkg
## generate the function reference HTML files with the command
## generate_package_html from the package `generate_html'
##
## Assumption: package generate_html is already installed
octave -q --eval \
"pkg install ${PkgTarGz}"
Doc="${Pkg}-html"
octave -q --eval \
"pkg load generate_html; generate_package_html ('${Pkg}', '${Doc}', 'octave-forge')"
octave -q --eval \
"pkg uninstall ${Pkg}"
## produce a tarball, take note of its checksum and encode it with
## uuencode
DocTarGz="${Doc}.tar.gz"
targz_md5_uue $DocTarGz $Doc
## List produced files in sandbox dir
echo $TmpDir
ls -l $TmpDir
ga-0.10.4/doc/ 0000755 0000000 0000000 00000000000 14616472453 007672 5 ustar 00 ga-0.10.4/doc/README 0000644 0000000 0000000 00000000461 14616472453 010553 0 ustar 00 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-0.10.4/inst/ 0000755 0000000 0000000 00000000000 14616472453 010102 5 ustar 00 ga-0.10.4/inst/__ga_crossoverfcn__.m 0000644 0000000 0000000 00000002435 14616472453 014243 0 ustar 00 ## 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 3 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-0.10.4/inst/__ga_initial_population__.m 0000644 0000000 0000000 00000007251 14616472453 015433 0 ustar 00 ## 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 3 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-0.10.4/inst/__ga_mutationfcn__.m 0000644 0000000 0000000 00000002273 14616472453 014056 0 ustar 00 ## 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 3 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-0.10.4/inst/__ga_popinitrange__.m 0000644 0000000 0000000 00000002141 14616472453 014220 0 ustar 00 ## 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 3 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-0.10.4/inst/__ga_problem__.m 0000644 0000000 0000000 00000010262 14616472453 013164 0 ustar 00 ## 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 3 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-0.10.4/inst/__ga_problem_private_state__.m 0000644 0000000 0000000 00000004166 14616472453 016124 0 ustar 00 ## 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 3 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-0.10.4/inst/__ga_problem_return_variables__.m 0000644 0000000 0000000 00000002630 14616472453 016613 0 ustar 00 ## 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 3 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
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-0.10.4/inst/__ga_problem_state_selection__.m 0000644 0000000 0000000 00000002572 14616472453 016436 0 ustar 00 ## 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 3 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-0.10.4/inst/__ga_problem_update_state_at_each_generation__.m 0000644 0000000 0000000 00000004243 14616472453 021607 0 ustar 00 ## 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 3 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-0.10.4/inst/__ga_scores__.m 0000644 0000000 0000000 00000004004 14616472453 013017 0 ustar 00 ## 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 3 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-0.10.4/inst/__ga_selectionfcn__.m 0000644 0000000 0000000 00000001672 14616472453 014205 0 ustar 00 ## 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 3 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-0.10.4/inst/__ga_stop__.m 0000644 0000000 0000000 00000002536 14616472453 012516 0 ustar 00 ## 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 3 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-0.10.4/inst/__gaoptimset_default_options__.m 0000644 0000000 0000000 00000005307 14616472453 016514 0 ustar 00 ## 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 3 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-0.10.4/inst/crossoverscattered.m 0000644 0000000 0000000 00000005234 14616472453 014210 0 ustar 00 ## Copyright (C) 2008, 2009, 2011 Luca Favatella
## Copyright (C) 2019-2020 John D
##
## 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 3 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: 7.1
## -*- texinfo -*-
## @deftypefn{Function File} {@var{xoverKids} =} crossoverscattered (@var{parents}, @var{options}, @var{nvars}, @var{FitnessFcn}, @var{unused}, @var{popuplation})
## Default crossover function for problems without linear constraints
##
## crossoverscattered creates a random binary vector and selects genes
## where the vector is a 1 from the first parent and a 0 from the next
## parent.
##
## @strong{Inputs}
## @table @var
## @item parents
## Row vector of parents chosen from selection function
## @item options
## options
## @item nvars
## Number of variables
## @item FitnessFcn
## Fitness function to use
## @item unused
## Placeholder variable not used
## @item population
## Matrix representing the current population
## @end table
##
## @strong{Outputs}
## @table @var
## @item xoverkids
## Crossover offspring matrix where roes correspond to children. The
## number of columns is the number of variables.
## @end table
##
## @seealso{ga}
## @end deftypefn
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 (2, n_children, nvars) - 1;
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-0.10.4/inst/fitscalingrank.m 0000644 0000000 0000000 00000005032 14616472453 013257 0 ustar 00 ## Copyright (C) 2008, 2009 Luca Favatella
## Copyright (C) 2019 John D
##
## 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 3 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: 1.3.4
## -*- texinfo -*-
## @deftypefn{Function File} {@var{expection} =} fitscalingrank (@var{scores}, @var{nParents})
## Default fitness scaling function
##
## fitscalingrank provides scaling based on rank instead of score.
##
## @strong{Inputs}
## @table @var
## @item scores
## A vector of scalars for each member of the population
## @item nParents
## The number of parents needs from the population
## @end table
##
## @strong{Outputs}
## @table @var
## @item expectation
## Column vector of same size as scores giving scaled values of each member of the population.
## @end table
##
## @seealso{ga}
## @end deftypefn
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-0.10.4/inst/ga.m 0000644 0000000 0000000 00000035537 14616472453 010664 0 ustar 00 ## 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 3 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 - 1]));
%! 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-0.10.4/inst/gacreationuniform.m 0000644 0000000 0000000 00000003736 14616472453 014005 0 ustar 00 ## 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 3 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-0.10.4/inst/gaoptimset.m 0000644 0000000 0000000 00000010624 14616472453 012437 0 ustar 00 ## Copyright (C) 2008, 2009, 2010 Luca Favatella
## Copyright (C) 2019 John D
##
## 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 3 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
## Default function is @@gacreationuniform
## @item CrossoverFcn
## Default function is @@crossoverscattered
## @item CrossoverFraction
## Default value is 0.0
## @item EliteCount
## Default value is 2
## @item FitnessLimit
## @item FitnessScalingFcn
## Default function is @@fitscalingrank
## @item Generations
## Default valie is 100
## @item InitialPopulation
## Can be partial.
## @item InitialScores
## column vector | [] (default) . Can be partial.
## @item MutationFcn
## Default mutation is @{ @@mutationgaussian, scale, shrink @}
##
## scale and shrink are 1.0
## @item PopInitRange
## @item PopulationSize
## @item SelectionFcn
## Default function is @@selectionstochunif
## @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: 4.4.8
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-0.10.4/inst/mutationgaussian.m 0000644 0000000 0000000 00000006055 14616472453 013661 0 ustar 00 ## Copyright (C) 2008 Luca Favatella
## Copyright (C) 2019 John D
##
## 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 3 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: 1.7.2
## -*- texinfo -*-
## @deftypefn{Function File} {@var{mutationChildren} =} mutationgaussian (@var{parents}, @var{options}, @var{nvars}, @var{FitnessFcn}, @var{state}, @var{thisScore}, {thisPopulation})
## Default mutation function
##
## mutationgaussian uses a random number from the gaussian distribution
## added to the mean to each entry of the parent
##
## @strong{Inputs}
## @table @var
## @item parents
## Row vector of parents chosen by a selection function
## @item options
## options
## @item nvars
## Number of variables
## @item FitnessFcn
## Fitness function
## @item state
## Structure containing information about current generation
## @item thsiScore
## vector of scores for the current population
## @item thisPopulation
## Matrix of individuals in the current population
## @end table
##
## @strong{Outputs}
## @table @var
## @item mutationChildren
## mutated offspring as a matrix where rows correspond to children,
## number of columns is the number of variables.
## @end table
##
## @seealso{ga}
## @end deftypefn
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-0.10.4/inst/rastriginsfcn.m 0000644 0000000 0000000 00000003664 14616472453 013145 0 ustar 00 ## Copyright (C) 2008, 2009, 2010, 2012 Luca Favatella
## Copyright (C) 2019-2021 John D
##
## 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 3 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.
##
## @strong{Inputs}
## @table @var
## @item x
## Input 2 column vector
## @end table
##
## @strong{Outputs}
## @table @var
## @item y
## result output using rastrigin's function
## @end table
##
## @seealso{ga}
## @end deftypefn
## Author: Luca Favatella
## Version: 2.0.1
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-0.10.4/inst/selectionstochunif.m 0000644 0000000 0000000 00000004414 14616472453 014173 0 ustar 00 ## Copyright (C) 2008 Luca Favatella
## Copyright (C) 2019 John D
##
## 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 3 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: 1.4
## -*- texinfo -*-
## @deftypefn{Function File} {@var{parents} =} selectionstochunuf (@var{expections}, @var{nParents}, @var{options})
## Default selection function
##
## Selection based uniform proportional steps based on its caled value.
##
## @strong{Inputs}
## @table @var
## @item expectation
## Column vector of scaled fitness for each member of a population.
## @item nParents
## The number of parents to select
## @item options
## ga options
## @end table
##
## @strong{Outputs}
## @table @var
## @item parents
## Row vector of size nParents containg the indices of selected parents.
## @end table
##
## @seealso{ga}
## @end deftypefn
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-0.10.4/inst/test_ga.m 0000644 0000000 0000000 00000002400 14616472453 011702 0 ustar 00 ## 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 3 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__