git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@177 331e1502-861f-0410-8da2-ba01fb791d7f

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legrand 2007-02-06 13:11:53 +00:00
commit f3bf6dcb10
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Arnaud Liefooghe
Thomas Legrand
Sébastien Cahon
Abdelhakim Deneche

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SUBDIRS = docs src tutorials
clean_all: clean_aux clean_doc
-@make clean
-@(rm -rf aclocal.m4 autom4te.cache configure config.* CO* dep* INST* install-sh miss* mkins* Makefile Makefile.in;\
cd docs; rm -rf Makefile Makefile.in *.doxytag; cd ../src ; rm -rf Makefile Makefile.in; cd ../tutorials; rm -rf Makefile Makefile.in;\
cd lesson1; rm -rf .deps/ Makefile Makefile.in)
clean_aux:
-@find . \( -name "*~" -o -name "*.old" -o -name "#*" -o -name "*.bak" \) -print -exec rm -rf \{\} \;
doc:
-@(cd docs; make doc)
clean_doc:
-@(cd docs; make clean-local)

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* release 0.1
# Local Variables:
# coding: iso-8859-1
# mode: text
# fill-column: 80
# End:

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PARADISEO-MOEO README FILE
=======================================================================
check latest news at http://paradiseo.gforge.inria.fr/
=======================================================================
Welcome to ParadisEO-MOEO, the Multi-Objective Evolving Objects library.
The latest news about ParadisEO-MOEO can be found on the gforge repository at
http://paradiseo.gforge.inria.fr/
In case of any problem, please e-mail us at
paradiseo-help@lists.gforge.inria.fr
==================================================================
BUILDING PARADISEO-MOEO
==================================================================
The basic installation procedure goes the following:
Go to your build-directory and run
> $(SRCDIR)/configure
> make
> make doc
where $(SRCDIR) is the top-level source directory of PARADISEO-MOEO,
i.e. where the sources were unpacked.
In case of problems, you can read the INSTALL file - but remember this
is a standard installation file from GNU and that it contains nothing
specific about PARADISEO-MOEO.
To clean everything, the simply run
> make clean_all
===================================================================
DIRECTORY STRUCTURE
===================================================================
After unpacking the archive file, you should end up with the following
structure:
.../ The main PARADISEO-MOEO directory, created when unpacking.
|
+-- src SOURCE directory Contains most PARADISEO-MOEO .h files.
|
+-- docs DOCUMENTATION directory (generated by Doxygen).
| |
| +- html HTML files - start at index.html.
| |
| +- latex latex files - use to generate Postcript doc.
| |
| +- man Unix man format documentation.
|
|
+-- tutorials APPLICATIONS - one directory per separate application.
|
+-- lesson1 A bi-objective flow-shop problem example with main algorithms.
| |
| +-benchmarks Instance files for testing.
|
|-- lesson2 Implement NSGA-II for the SCH1 problem.
===================================================================
NOTES
===================================================================
Mailing list : paradiseo-help@lists.gforge.inria.fr

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#!/bin/sh
# Run this to generate all the initial makefiles, etc.
srcdir=`dirname $0`
PKG_NAME="the package."
DIE=0
(autoconf --version) < /dev/null > /dev/null 2>&1 || {
echo
echo "**Error**: You must have \`autoconf' installed to."
echo "Download the appropriate package for your distribution,"
echo "or get the source tarball at ftp://ftp.gnu.org/pub/gnu/"
DIE=1
}
(grep "^AM_PROG_LIBTOOL" $srcdir/configure.in >/dev/null) && {
(libtool --version) < /dev/null > /dev/null 2>&1 || {
echo
echo "**Error**: You must have \`libtool' installed."
echo "Get ftp://ftp.gnu.org/pub/gnu/libtool-1.2d.tar.gz"
echo "(or a newer version if it is available)"
DIE=1
}
}
grep "^AM_GNU_GETTEXT" $srcdir/configure.in >/dev/null && {
grep "sed.*POTFILES" $srcdir/configure.in >/dev/null || \
(gettext --version) < /dev/null > /dev/null 2>&1 || {
echo
echo "**Error**: You must have \`gettext' installed."
echo "Get ftp://alpha.gnu.org/gnu/gettext-0.10.35.tar.gz"
echo "(or a newer version if it is available)"
DIE=1
}
}
grep "^AM_GNOME_GETTEXT" $srcdir/configure.in >/dev/null && {
grep "sed.*POTFILES" $srcdir/configure.in >/dev/null || \
(gettext --version) < /dev/null > /dev/null 2>&1 || {
echo
echo "**Error**: You must have \`gettext' installed."
echo "Get ftp://alpha.gnu.org/gnu/gettext-0.10.35.tar.gz"
echo "(or a newer version if it is available)"
DIE=1
}
}
(automake --version) < /dev/null > /dev/null 2>&1 || {
echo
echo "**Error**: You must have \`automake' installed."
echo "Get ftp://ftp.gnu.org/pub/gnu/automake-1.3.tar.gz"
echo "(or a newer version if it is available)"
DIE=1
NO_AUTOMAKE=yes
}
# if no automake, don't bother testing for aclocal
test -n "$NO_AUTOMAKE" || (aclocal --version) < /dev/null > /dev/null 2>&1 || {
echo
echo "**Error**: Missing \`aclocal'. The version of \`automake'"
echo "installed doesn't appear recent enough."
echo "Get ftp://ftp.gnu.org/pub/gnu/automake-1.3.tar.gz"
echo "(or a newer version if it is available)"
DIE=1
}
if test "$DIE" -eq 1; then
exit 1
fi
if test -z "$*"; then
echo "**Warning**: I am going to run \`configure' with no arguments."
echo "If you wish to pass any to it, please specify them on the"
echo \`$0\'" command line."
echo
fi
case $CC in
xlc )
am_opt=--include-deps;;
esac
for coin in `find $srcdir -name configure.in -print`
do
dr=`dirname $coin`
if test -f $dr/NO-AUTO-GEN; then
echo skipping $dr -- flagged as no auto-gen
else
echo processing $dr
macrodirs=`sed -n -e 's,AM_ACLOCAL_INCLUDE(\(.*\)),\1,gp' < $coin`
( cd $dr
aclocalinclude="$ACLOCAL_FLAGS"
for k in $macrodirs; do
if test -d $k; then
aclocalinclude="$aclocalinclude -I $k"
##else
## echo "**Warning**: No such directory \`$k'. Ignored."
fi
done
if grep "^AM_GNU_GETTEXT" configure.in >/dev/null; then
if grep "sed.*POTFILES" configure.in >/dev/null; then
: do nothing -- we still have an old unmodified configure.in
else
echo "Creating $dr/aclocal.m4 ..."
test -r $dr/aclocal.m4 || touch $dr/aclocal.m4
echo "Running gettextize... Ignore non-fatal messages."
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echo "Making $dr/aclocal.m4 writable ..."
test -r $dr/aclocal.m4 && chmod u+w $dr/aclocal.m4
fi
fi
if grep "^AM_GNOME_GETTEXT" configure.in >/dev/null; then
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echo "Running gettextize... Ignore non-fatal messages."
echo "no" | gettextize --force --copy
echo "Making $dr/aclocal.m4 writable ..."
test -r $dr/aclocal.m4 && chmod u+w $dr/aclocal.m4
fi
if grep "^AM_PROG_LIBTOOL" configure.in >/dev/null; then
echo "Running libtoolize..."
libtoolize --force --copy
fi
echo "Running aclocal $aclocalinclude ..."
aclocal $aclocalinclude
if grep "^AM_CONFIG_HEADER" configure.in >/dev/null; then
echo "Running autoheader..."
autoheader
fi
echo "Running automake --gnu $am_opt ..."
automake --add-missing --gnu $am_opt
echo "Running autoconf ..."
autoconf
)
fi
done
#conf_flags="--enable-maintainer-mode --enable-compile-warnings" #--enable-iso-c
if test x$NOCONFIGURE = x; then
echo Running $srcdir/configure $conf_flags "$@" ...
$srcdir/configure $conf_flags "$@" \
&& echo Now type \`make\' to compile $PKG_NAME
else
echo Skipping configure process.
fi

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AC_INIT(configure.in)
AM_INIT_AUTOMAKE(moeo, 0.1)
AC_ISC_POSIX
AC_PROG_CXX
AM_PROG_CC_STDC
AC_HEADER_STDC
AC_PROG_RANLIB
AC_PROG_INSTALL
AC_PROG_LN_S
AC_PROG_MAKE_SET
AC_C_CONST
AC_C_INLINE
AC_TYPE_SIZE_T
AC_SUBST(EO_DIR)
dnl EO
AC_ARG_WITH(EOdir,
--with-EOdir : Giving the path of the EO tree.,
EO_DIR="$withval"
if test ! -d $EO_DIR
then
echo ""
echo "# --with-EOdir Invalid directory $withval"
exit 1
fi,
echo ""
echo "# You forgot to give the path of the EO tree !"
echo "# Please write something like ... './configure --with-EOdir=\$HOME/eo'"
exit 1
)
AC_OUTPUT([
Makefile
src/Makefile
docs/Makefile
tutorials/Makefile
tutorials/lesson1/Makefile
tutorials/lesson2/Makefile
])

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doc:
-@doxygen moeo.doxyfile
clean-local:
rm -rf html latex man

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/** @mainpage Welcome to ParadisEO-MOEO
@section intro Introduction
ParadisEO-MOEO is a white-box object-oriented generic framework dedicated to the flexible design of evolutionary multi-objective algorithms.
This paradigm-free software embeds some features and techniques for Pareto-based resolution and
aims to provide a set of classes allowing to ease and speed up the development of computationally efficient programs.
It is based on a clear conceptual distinction between the solution methods and the multi-objective problems they are intended to solve.
This separation confers a maximum design and code reuse.
ParadisEO-MOEO provides a broad range of archive-related features (such as elitism or performance metrics)
and the most common Pareto-based fitness assignment strategies (MOGA, NSGA, SPEA, IBEA and more).
Furthermore, parallel and distributed models as well as hybridization mechanisms can be applied to an algorithm designed within ParadisEO-MOEO
using the whole version of ParadisEO.
@section tutorial Tutorial
A tutorial about a bi-objective flow-shop scheduling problem will be available soon.
@section install Installation
The installation procedure of the package is detailed in the <a
href="../../README">README</a> file in the top-directory of the source-tree.
@section design Overall Design
For an introduction to the design of ParadisEO-MOEO,
you can look at the <a href="http://paradiseo.gforge.inria.fr">ParadisEO website</a>.
*/
/** @page webpages Related webpages
- ParadisEO <a href="http://paradiseo.gforge.inria.fr">homepage</a>
- INRIA GForge <a href="http://gforge.inria.fr/projects/paradiseo/">project page</a>
- <a href="../../README">README</a>
- <a href="../../NEWS">NEWS</a>
*/
// Local Variables:
// coding: iso-8859-1
// mode: C++
// c-file-style: "Stroustrup"
// fill-column: 80
// End:

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WARN_IF_UNDOCUMENTED = YES
WARN_IF_DOC_ERROR = YES
WARN_NO_PARAMDOC = NO
WARN_FORMAT = "$file:$line: $text"
WARN_LOGFILE =
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# configuration options related to the input files
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INPUT = . ../src
FILE_PATTERNS = *.cpp \
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NEWS README
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COLS_IN_ALPHA_INDEX = 3
IGNORE_PREFIX = moeo
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HTML_OUTPUT = html
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COMPACT_RTF = NO
RTF_HYPERLINKS = NO
RTF_STYLESHEET_FILE =
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# configuration options related to the man page output
#---------------------------------------------------------------------------
GENERATE_MAN = YES
MAN_OUTPUT = man
MAN_EXTENSION = .3
MAN_LINKS = NO
#---------------------------------------------------------------------------
# configuration options related to the XML output
#---------------------------------------------------------------------------
GENERATE_XML = NO
XML_OUTPUT = xml
XML_SCHEMA =
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#---------------------------------------------------------------------------
# configuration options for the AutoGen Definitions output
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// MOEO.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEO_H_
#define MOEO_H_
#include <iostream>
#include <stdexcept>
#include <string>
#include <EO.h>
/**
* Base class allowing to represent a solution (an individual) for multi-objective optimization.
* The template argument MOEOObjectiveVector allows to represent the solution in the objective space (it can be a moeoObjectiveVector object).
* The template argument MOEOFitness is an object reflecting the quality of the solution in term of convergence (the fitness of a solution is always to be maximized).
* The template argument MOEODiversity is an object reflecting the quality of the solution in term of diversity (the diversity of a solution is always to be maximized).
* All template arguments must have a void and a copy constructor.
* Besides, note that, contrary to the mono-objective case (and to EO) where the fitness value of a solution is confused with its objective value,
* the fitness value differs of the objectives values in the multi-objective case.
*
* !!!!!!!!!!!!!!!!! !!!!!
* operator '<' et '>' ???
* !!!!!!!!!!!!!!!!!!!!!!!
*/
template < class MOEOObjectiveVector, class MOEOFitness, class MOEODiversity >
class MOEO : public EO < MOEOFitness >
{
public:
/** the objective vector type of a solution */
typedef MOEOObjectiveVector ObjectiveVector;
/** the fitness type of a solution */
typedef MOEOFitness Fitness;
/** the diversity type of a solution */
typedef MOEODiversity Diversity;
/**
* Ctor
*/
MOEO()
{
// default values for every parameters
objectiveVectorValue = ObjectiveVector();
fitnessValue = Fitness();
diversityValue = Diversity();
// invalidate all
invalidate();
}
/**
* Virtual dtor
*/
virtual ~MOEO() {};
/**
* Returns the objective vector of the current solution
*/
ObjectiveVector objectiveVector() const
{
if ( invalidObjectiveVector() )
{
throw std::runtime_error("invalid objective vector");
}
return objectiveVectorValue;
}
/**
* Sets the objective vector of the current solution
* @param _objectiveVectorValue the new objective vector
*/
void objectiveVector(const ObjectiveVector & _objectiveVectorValue)
{
objectiveVectorValue = _objectiveVectorValue;
invalidObjectiveVectorValue = false;
}
/**
* Sets the objective vector as invalid
*/
void invalidateObjectiveVector()
{
invalidObjectiveVectorValue = true;
}
/**
* Returns true if the objective vector is invalid, false otherwise
*/
bool invalidObjectiveVector() const
{
return invalidObjectiveVectorValue;
}
/**
* Returns the fitness value of the current solution
*/
Fitness fitness() const
{
if ( invalidFitness() )
{
throw std::runtime_error("invalid fitness");
}
return fitnessValue;
}
/**
* Sets the fitness value of the current solution
* @param _fitnessValue the new fitness value
*/
void fitness(const Fitness & _fitnessValue)
{
fitnessValue = _fitnessValue;
invalidFitnessValue = false;
}
/**
* Sets the fitness value as invalid
*/
void invalidateFitness()
{
invalidFitnessValue = true;
}
/**
* Returns true if the fitness value is invalid, false otherwise
*/
bool invalidFitness() const
{
return invalidFitnessValue;
}
/**
* Returns the diversity value of the current solution
*/
Diversity diversity() const
{
if ( invalidDiversity() )
{
throw std::runtime_error("invalid diversity");
}
return diversityValue;
}
/**
* Sets the diversity value of the current solution
* @param _diversityValue the new diversity value
*/
void diversity(const Diversity & _diversityValue)
{
diversityValue = _diversityValue;
invalidDiversityValue = false;
}
/**
* Sets the diversity value as invalid
*/
void invalidateDiversity()
{
invalidDiversityValue = true;
}
/**
* Returns true if the diversity value is invalid, false otherwise
*/
bool invalidDiversity() const
{
return invalidDiversityValue;
}
/**
* Sets the objective vector, the fitness value and the diversity value as invalid
*/
void invalidate()
{
invalidateObjectiveVector();
invalidateFitness();
invalidateDiversity();
}
/**
* Returns true if the fitness value is invalid, false otherwise
*/
bool invalid() const
{
return invalidObjectiveVector();
}
/**
* Return the class id (the class name as a std::string)
*/
virtual std::string className() const
{
return "MOEO";
}
/**
* Writing object
* @param _os output stream
*/
virtual void printOn(std::ostream & _os) const
{
if ( invalidObjectiveVector() )
{
_os << "INVALID\t";
}
else
{
_os << objectiveVectorValue << '\t';
}
}
/**
* Reading object
* @param _is input stream
*/
virtual void readFrom(std::istream & _is)
{
std::string objectiveVector_str;
int pos = _is.tellg();
_is >> objectiveVector_str;
if (objectiveVector_str == "INVALID")
{
invalidateObjectiveVector();
}
else
{
invalidObjectiveVectorValue = false;
_is.seekg(pos); // rewind
_is >> objectiveVectorValue;
}
}
private:
/** the objective vector of this solution */
ObjectiveVector objectiveVectorValue;
/** true if the objective vector is invalid */
bool invalidObjectiveVectorValue;
/** the fitness value of this solution */
Fitness fitnessValue;
/** true if the fitness value is invalid */
bool invalidFitnessValue;
/** the diversity value of this solution */
Diversity diversityValue;
/** true if the diversity value is invalid */
bool invalidDiversityValue;
};
#endif /*MOEO_H_*/

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# Nothing to compile !

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoAdditiveEpsilonBinaryMetric.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOADDITIVEEPSILONBINARYMETRIC_H_
#define MOEOADDITIVEEPSILONBINARYMETRIC_H_
#include <metric/moeoMetric.h>
/**
*
*/
template < class MOEOT >
class moeoAdditiveEpsilonBinaryMetric : public moeoSolutionVsSolutionBinaryMetric < MOEOT, double >
{
public:
/** the objective vector type of a solution */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
moeoAdditiveEpsilonBinaryMetric();
double operator()(const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2)
{
}
};
#endif /*MOEOADDITIVEEPSILONBINARYMETRIC_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoBinaryMetricSavingUpdater.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2006
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOBINARYMETRICSAVINGUPDATER_H_
#define MOEOBINARYMETRICSAVINGUPDATER_H_
#include <fstream>
#include <string>
#include <eoPop.h>
#include <utils/eoUpdater.h>
#include <metric/moeoMetric.h>
/**
* This class allows to save the progression of a binary metric comparing the fitness values of the current population (or archive)
* with the fitness values of the population (or archive) of the generation (n-1) into a file
*/
template <class EOT>
class moeoBinaryMetricSavingUpdater : public eoUpdater
{
public:
/**
* The fitness type of a solution
*/
typedef typename EOT::ObjectiveVector ObjectiveVector;
/**
* Ctor
* @param _metric the binary metric comparing two Pareto sets
* @param _pop the main population
* @param _filename the target filename
*/
moeoBinaryMetricSavingUpdater (moeoPopVsPopBinaryMetric<EOT,double> & _metric, const eoPop<EOT> & _pop, std::string _filename) :
metric(_metric), pop(_pop), filename(_filename), counter(1)
{}
/**
* Saves the metric's value for the current generation
*/
void operator()() {
if (pop.size()) {
if (firstGen) {
firstGen = false;
}
else {
// creation of the two Pareto sets
/*
std::vector<ObjectiveVector> from;
std::vector<ObjectiveVector> to;
for (unsigned i=0; i<pop.size(); i++)
from.push_back(pop[i].objectiveVector());
for (unsigned i=0 ; i<oldPop.size(); i++)
to.push_back(oldPop[i].objectiveVector());
*/
// writing the result into the file
std::ofstream f (filename.c_str(), std::ios::app);
f << counter++ << ' ' << metric(pop,oldPop) << std::endl;
f.close();
}
oldPop = pop;
}
}
private:
/** binary metric comparing two Pareto sets */
moeoPopVsPopBinaryMetric<EOT,double> & metric;
/** main population */
const eoPop<EOT> & pop;
/** (n-1) population */
eoPop<EOT> oldPop;
/** target filename */
std::string filename;
/** is it the first generation ? */
bool firstGen;
/** counter */
unsigned counter;
};
#endif /*MOEOBINARYMETRICSAVINGUPDATER_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoContributionMetric.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2006
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOCONTRIBUTIONMETRIC_H_
#define MOEOCONTRIBUTIONMETRIC_H_
#include <metric/moeoMetric.h>
/**
* The contribution metric evaluates the proportion of non-dominated solutions given by a Pareto set relatively to another Pareto set
*
* (Meunier, Talbi, Reininger: 'A multiobjective genetic algorithm for radio network optimization', in Proc. of the 2000 Congress on Evolutionary Computation, IEEE Press, pp. 317-324)
*/
template < class MOEOT >
class moeoContributionMetric : public moeoPopVsPopBinaryMetric < MOEOT, double >
{
public:
/** the objective vector type of a solution */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Returns the contribution of the Pareto set '_set1' relatively to the Pareto set '_set2'
* @param _set1 the first Pareto set
* @param _set2 the second Pareto set
*/
double operator()(const eoPop < MOEOT > & _pop1, const eoPop < MOEOT > & _pop2) {
/************/
std::vector<ObjectiveVector> set1;
std::vector<ObjectiveVector> set2;
for (unsigned i=0; i<_pop1.size(); i++)
set1.push_back(_pop1[i].objectiveVector());
for (unsigned i=0 ; i<_pop2.size(); i++)
set2.push_back(_pop2[i].objectiveVector());
/****************/
unsigned c = card_C(set1, set2);
unsigned w1 = card_W(set1, set2);
unsigned n1 = card_N(set1, set2);
unsigned w2 = card_W(set2, set1);
unsigned n2 = card_N(set2, set1);
return (double) (c / 2.0 + w1 + n1) / (c + w1 + n1 + w2 + n2);
}
private:
/**
* Returns the number of solutions both in '_set1' and '_set2'
* @param _set1 the first Pareto set
* @param _set2 the second Pareto set
*/
unsigned card_C (const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2) {
unsigned c=0;
for (unsigned i=0; i<_set1.size(); i++)
for (unsigned j=0; j<_set2.size(); j++)
if (_set1[i] == _set2[j]) {
c++;
break;
}
return c;
}
/**
* Returns the number of solutions in '_set1' dominating at least one solution of '_set2'
* @param _set1 the first Pareto set
* @param _set2 the second Pareto set
*/
unsigned card_W (const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2) {
unsigned w=0;
for (unsigned i=0; i<_set1.size(); i++)
for (unsigned j=0; j<_set2.size(); j++)
if (_set1[i].dominates(_set2[j])) {
w++;
break;
}
return w;
}
/**
* Returns the number of solutions in '_set1' having no relation of dominance with those from '_set2'
* @param _set1 the first Pareto set
* @param _set2 the second Pareto set
*/
unsigned card_N (const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2) {
unsigned n=0;
for (unsigned i=0; i<_set1.size(); i++) {
bool domin_rel = false;
for (unsigned j=0; j<_set2.size(); j++)
if (_set1[i].dominates(_set2[j]) || _set2[j].dominates(_set1 [i])) {
domin_rel = true;
break;
}
if (! domin_rel)
n++;
}
return n;
}
};
#endif /*MOEOCONTRIBUTIONMETRIC_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoEntropyMetric.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2006
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOENTROPYMETRIC_H_
#define MOEOENTROPYMETRIC_H_
#include <metric/moeoMetric.h>
/**
* The entropy gives an idea of the diversity of a Pareto set relatively to another Pareto set
*
* (Basseur, Seynhaeve, Talbi: 'Design of Multi-objective Evolutionary Algorithms: Application to the Flow-shop Scheduling Problem', in Proc. of the 2002 Congress on Evolutionary Computation, IEEE Press, pp. 1155-1156)
*/
template < class MOEOT >
class moeoEntropyMetric : public moeoVectorVsVectorBinaryMetric < MOEOT, double >
{
public:
/** the objective vector type of a solution */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Returns the entropy of the Pareto set '_set1' relatively to the Pareto set '_set2'
* @param _set1 the first Pareto set
* @param _set2 the second Pareto set
*/
double operator()(const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2) {
// normalization
std::vector< ObjectiveVector > set1 = _set1;
std::vector< ObjectiveVector > set2= _set2;
removeDominated (set1);
removeDominated (set2);
prenormalize (set1);
normalize (set1);
normalize (set2);
// making of PO*
std::vector< ObjectiveVector > star; // rotf :-)
computeUnion (set1, set2, star);
removeDominated (star);
// making of PO1 U PO*
std::vector< ObjectiveVector > union_set1_star; // rotf again ...
computeUnion (set1, star, union_set1_star);
unsigned C = union_set1_star.size();
float omega=0;
float entropy=0;
for (unsigned i=0 ; i<C ; i++) {
unsigned N_i = howManyInNicheOf (union_set1_star, union_set1_star[i], star.size());
unsigned n_i = howManyInNicheOf (set1, union_set1_star[i], star.size());
if (n_i > 0) {
omega += 1.0 / N_i;
entropy += (float) n_i / (N_i * C) * log (((float) n_i / C) / log (2.0));
}
}
entropy /= - log (omega);
entropy *= log (2.0);
return entropy;
}
private:
std::vector<double> vect_min_val;
std::vector<double> vect_max_val;
void removeDominated(std::vector< ObjectiveVector > & _f) {
for (unsigned i=0 ; i<_f.size(); i++) {
bool dom = false;
for (unsigned j=0; j<_f.size(); j++)
if (i != j && _f[j].dominates(_f[i])) {
dom = true;
break;
}
if (dom) {
_f[i] = _f.back();
_f.pop_back();
i--;
}
}
}
void prenormalize (const std::vector< ObjectiveVector > & _f) {
vect_min_val.clear();
vect_max_val.clear();
for (unsigned char i=0 ; i<ObjectiveVector::nObjectives(); i++) {
float min_val = _f.front()[i], max_val = min_val;
for (unsigned j=1 ; j<_f.size(); j++) {
if (_f[j][i] < min_val)
min_val = _f[j][i];
if (_f[j][i]>max_val)
max_val = _f[j][i];
}
vect_min_val.push_back(min_val);
vect_max_val.push_back (max_val);
}
}
void normalize (std::vector< ObjectiveVector > & _f) {
for (unsigned i=0 ; i<ObjectiveVector::nObjectives(); i++)
for (unsigned j=0; j<_f.size(); j++)
_f[j][i] = (_f[j][i] - vect_min_val[i]) / (vect_max_val[i] - vect_min_val[i]);
}
void computeUnion(const std::vector< ObjectiveVector > & _f1, const std::vector< ObjectiveVector > & _f2, std::vector< ObjectiveVector > & _f) {
_f = _f1 ;
for (unsigned i=0; i<_f2.size(); i++) {
bool b = false;
for (unsigned j=0; j<_f1.size(); j ++)
if (_f1[j] == _f2[i]) {
b = true;
break;
}
if (! b)
_f.push_back(_f2[i]);
}
}
unsigned howManyInNicheOf (const std::vector< ObjectiveVector > & _f, const ObjectiveVector & _s, unsigned _size) {
unsigned n=0;
for (unsigned i=0 ; i<_f.size(); i++) {
if (euclidianDistance(_f[i], _s) < (_s.size() / (double) _size))
n++;
}
return n;
}
double euclidianDistance (const ObjectiveVector & _set1, const ObjectiveVector & _to, unsigned _deg = 2) {
double dist=0;
for (unsigned i=0; i<_set1.size(); i++)
dist += pow(fabs(_set1[i] - _to[i]), (int)_deg);
return pow(dist, 1.0 / _deg);
}
};
#endif /*MOEOENTROPYMETRIC_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoMetric.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOMETRIC_H_
#define MOEOMETRIC_H_
#include <eoFunctor.h>
/**
* Base class for performance metrics (also called quality indicators)
*/
class moeoMetric : public eoFunctorBase
{};
/**
* Base class for unary metrics
*/
template < class A, class R >
class moeoUnaryMetric : public eoUF < A, R >, public moeoMetric
{};
/**
* Base class for binary metrics
*/
template < class A1, class A2, class R >
class moeoBinaryMetric : public eoBF < A1, A2, R >, public moeoMetric
{};
/**
* Base class for unary metrics dedicated to the performance evaluation of a single solution's Pareto fitness
*/
template < class MOEOT, class R>//, class ObjVector = typename MOEOT::ObjectiveVector >
//class moeoSolutionUnaryMetric : public moeoUnaryMetric < const ObjVector &, R >
class moeoSolutionUnaryMetric : public moeoUnaryMetric < const MOEOT &, R >
{};
/**
* Base class for unary metrics dedicated to the performance evaluation of a Pareto set (a vector of Pareto fitnesses)
*/
template < class MOEOT, class R>//, class ObjVector = typename MOEOT::ObjectiveVector >
//class moeoVectorUnaryMetric : public moeoUnaryMetric < const std::vector < ObjVector > &, R >
class moeoPopUnaryMetric : public moeoUnaryMetric < const eoPop < MOEOT > &, R >
{};
/**
* Base class for binary metrics dedicated to the performance comparison between two solutions's Pareto fitnesses
*/
template < class MOEOT, class R>//, class ObjVector = typename MOEOT::ObjectiveVector >
//class moeoSolutionVsSolutionBinaryMetric : public moeoBinaryMetric < const ObjVector &, const ObjVector &, R >
class moeoSolutionVsSolutionBinaryMetric : public moeoBinaryMetric < const MOEOT &, const MOEOT &, R >
{};
/**
* Base class for binary metrics dedicated to the performance comparison between a Pareto set (a vector of Pareto fitnesses) and a single solution's Pareto fitness
*/
template < class MOEOT, class R>//, class ObjVector = typename MOEOT::ObjectiveVector >
//class moeoVectorVsSolutionBinaryMetric : public moeoBinaryMetric < const std::vector < ObjVector > &, const ObjVector &, R >
class moeoPopVsSolutionBinaryMetric : public moeoBinaryMetric < const eoPop < MOEOT > &, const MOEOT &, R >
{};
/**
* Base class for binary metrics dedicated to the performance comparison between two Pareto sets (two vectors of Pareto fitnesses)
*/
template < class MOEOT, class R >//, class ObjVector = typename MOEOT::ObjectiveVector >
//class moeoVectorVsVectorBinaryMetric : public moeoBinaryMetric < const std::vector < ObjVector > &, const std::vector < ObjVector > &, R >
class moeoPopVsPopBinaryMetric : public moeoBinaryMetric < const eoPop < MOEOT > &, const eoPop < MOEOT > &, R >
{};
#endif /*MOEOMETRIC_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeo
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEO_
#define MOEO_
#include <eo>
#include <metric/moeoBinaryMetricSavingUpdater.h>
#include <metric/moeoContributionMetric.h>
#include <metric/moeoEntropyMetric.h>
#include <metric/moeoMetric.h>
#include <moeoArchiveFitnessSavingUpdater.h>
#include <moeoArchiveUpdater.h>
#include <moeoArchive.h>
#include <moeoCombinedLS.h>
#include <moeoComparator.h>
#include <moeoDiversityAssignment.h>
#include <moeoEA.h>
#include <moeoEvalFunc.h>
#include <moeoFastNonDominatedSortingFitnessAssignment.h>
#include <moeoGenerationalReplacement.h>
#include <moeoHybridLS.h>
#include <moeoLS.h>
#include <moeoObjectiveVectorComparator.h>
#include <moeoObjectiveVectorTraits.h>
#include <moeoObjectiveVector.h>
#include <moeoRandomSelectOne.h>
#include <moeoReplacement.h>
#include <moeoSelectOneFromPopAndArch.h>
#include <moeoSelectOne.h>
#include <MOEO.h>
#endif /*MOEO_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoArchive.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOARCHIVE_H_
#define MOEOARCHIVE_H_
#include <eoPop.h>
/**
* An archive is a secondary population that stores non-dominated solutions
*/
template < class MOEOT >
class moeoArchive : public eoPop < MOEOT >
{
public:
using std::vector< MOEOT > :: size;
using std::vector< MOEOT > :: operator[];
using std::vector< MOEOT > :: back;
using std::vector< MOEOT > :: pop_back;
/**
* The type of an objective vector for a solution
*/
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Default ctor.
* The moeoObjectiveVectorComparator used to compare solutions is based on Pareto dominance
*/
moeoArchive() : eoPop < MOEOT >(), comparator(paretoComparator)
{}
/**
* Ctor
* @param _comparator the moeoObjectiveVectorComparator used to compare solutions
*/
moeoArchive(moeoObjectiveVectorComparator < ObjectiveVector > & _comparator) : eoPop < MOEOT >(), comparator(_comparator)
{}
/**
* Returns true if the current archive dominates _objectiveVector according to the moeoObjectiveVectorComparator given in the constructor
* @param _objectiveVector the objective vector to compare with the current archive
*/
bool dominates (const ObjectiveVector & _objectiveVector) const
{
for (unsigned i = 0; i < size(); i++)
{
if ( comparator(operator[](i).fitness(), _objectiveVector)==1 )
{
return true;
}
}
return false;
}
/**
* Returns true if the current archive already contains a solution with the same objective values than _objectiveVector
* @param _objectiveVector the objective vector to compare with the current archive
*/
bool contains (const ObjectiveVector & _objectiveVector) const
{
for (unsigned i = 0; i < size; i++)
{
if (operator[](i).fitness () == _objectiveVector)
{
return true;
}
}
return false;
}
/**
* Updates the archive with a given individual _moeo
* @param _moeo the given individual
*/
void update (const MOEOT & _moeo)
{
// first step: removing the dominated solutions from the archive
for (unsigned j = 0; j < size();)
{
// if _moeo.fitness() dominates operator[](j).fitness()
//if ( comparator(_moeo.fitness(), operator[](j).fitness())==1 )
if ( comparator(_moeo.objectiveVector(), operator[](j).objectiveVector())==1 )
{
operator[](j) = back();
pop_back();
}
//else if (_moeo.fitness() == operator[](j).fitness())
else if (_moeo.objectiveVector() == operator[](j).objectiveVector())
{
operator[](j) = back();
pop_back();
}
else
{
j++;
}
}
// second step: is _moeo dominated?
bool dom = false;
for (unsigned j=0; j<size(); j++)
{
// if operator[](j).fitness() dominates _moeo.fitness()
//if ( comparator(operator[](j).fitness(), _moeo.fitness())==1 )
if ( comparator(operator[](j).objectiveVector(), _moeo.objectiveVector())==1 )
{
dom = true;
break;
}
}
if (!dom)
{
push_back(_moeo);
}
}
/**
* Updates the archive with a given population _pop
* @param _pop the given population
*/
void update (const eoPop < MOEOT > & _pop)
{
for (unsigned i=0; i<_pop.size(); i++)
{
update(_pop[i]);
}
}
private:
/** The moeoObjectiveVectorComparator used to compare solutions */
moeoObjectiveVectorComparator < ObjectiveVector > & comparator;
/** A moeoObjectiveVectorComparator based on Pareto dominance (used as default) */
moeoParetoObjectiveVectorComparator < ObjectiveVector > paretoComparator;
};
#endif /*MOEOARCHIVE_H_ */

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoArchiveFitnessSavingUpdater.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2006
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOARCHIVEFITNESSSAVINGUPDATER_H_
#define MOEOARCHIVEFITNESSSAVINGUPDATER_H_
#include <fstream>
#include <string>
#include <eoPop.h>
#include <utils/eoUpdater.h>
#include <moeoArchive.h>
#define MAX_BUFFER_SIZE 1000
/**
* This class allows to save the fitnesses of solutions contained in an archive into a file at each generation.
*/
template <class EOT>
class moeoArchiveFitnessSavingUpdater : public eoUpdater
{
public:
/**
* Ctor
* @param _arch local archive
* @param _filename target filename
* @param _id own ID
*/
moeoArchiveFitnessSavingUpdater (moeoArchive<EOT> & _arch, const std::string & _filename = "Res/Arch", int _id = -1) : arch(_arch), filename(_filename), id(_id), counter(0)
{}
/**
* Saves the fitness of the archive's members into the file
*/
void operator()() {
char buff[MAX_BUFFER_SIZE];
if (id == -1)
sprintf (buff, "%s.%u", filename.c_str(), counter ++);
else
sprintf (buff, "%s.%u.%u", filename.c_str(), id, counter ++);
std::ofstream f(buff);
for (unsigned i = 0; i < arch.size (); i++)
f << arch[i].objectiveVector() << std::endl;
f.close ();
}
private:
/** local archive */
moeoArchive<EOT> & arch;
/** target filename */
std::string filename;
/** own ID */
int id;
/** counter */
unsigned counter;
};
#endif /*MOEOARCHIVEFITNESSSAVINGUPDATER_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoArchiveUpdater.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2006
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOARCHIVEUPDATER_H_
#define MOEOARCHIVEUPDATER_H_
#include <eoPop.h>
#include <utils/eoUpdater.h>
#include <moeoArchive.h>
/**
* This class allows to update the archive at each generation with newly found non-dominated solutions
*/
template < class EOT >
class moeoArchiveUpdater : public eoUpdater
{
public:
/**
* Ctor
* @param _arch an archive of non-dominated solutions
* @param _pop the main population
*/
moeoArchiveUpdater(moeoArchive <EOT> & _arch, const eoPop<EOT> & _pop) : arch(_arch), pop(_pop)
{}
/**
* Updates the archive with newly found non-dominated solutions contained in the main population
*/
void operator()() {
arch.update(pop);
}
private:
/** the archive of non-dominated solutions */
moeoArchive<EOT> & arch;
/** the main population */
const eoPop<EOT> & pop;
};
#endif /*MOEOARCHIVEUPDATER_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoCombinedLS.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOCOMBINEDLS_H_
#define MOEOCOMBINEDLS_H_
#include <moeoArchive.h>
#include <moeoEvalFunc.h>
#include <moeoLS.h>
/**
* This class allows to embed a set of local searches that are sequentially applied,
* and so working and updating the same archive of non-dominated solutions
*/
template < class MOEOT >
class moeoCombinedLS : public moeoLS < MOEOT > {
public:
/**
* Ctor
* @param _eval the full evaluator of a solution
* @param _first_ls the first multi-objective local search to add
*/
moeoCombinedLS(moeoEvalFunc < MOEOT > & _eval, moeoLS < MOEOT > & _first_ls) : eval (_eval) {
combinedLS.push_back (& _first_ls);
}
/**
* Adds a new local search to combine
* @param _ls the multi-objective local search to add
*/
void add(moeoLS < MOEOT > & _ls) {
combinedMOLS.push_back(& _ls);
}
/**
* Gives a new solution in order to explore the neigborhood.
* The new non-dominated solutions are added to the archive
* @param _eo the solution
* @param _arch the archive of non-dominated solutions
*/
void operator () (const MOEOT & _eo, moeoArchive < MOEOT > & _arch) {
eval(const_cast < MOEOT & > (_eo));
for (unsigned i=0; i<combinedLS.size(); i++)
combinedLS[i] -> operator()(_eo, _arch);
}
private:
/** the full evaluator of a solution */
moeoEvalFunc < MOEOT > & eval;
/** the vector that contains the combined LS */
std::vector< moeoLS < MOEOT > * > combinedLS;
};
#endif /*MOEOCOMBINEDLS_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoComparator.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOPOPSORTER_H_
#define MOEOPOPSORTER_H_
#include <eoFunctor.h>
#include <eoPop.h>
/**
* Functor allowing to compare two solutions
*/
template < class MOEOT >
class moeoComparator : public eoBF < const MOEOT &, const MOEOT &, const bool >
{};
/**
* Functor allowing to compare two solutions according to their first objective value, then their second, and so on
*/
template < class MOEOT >
class moeoObjectiveComparator : public moeoComparator < MOEOT >
{
public:
/**
* Returns true if _moeo1 is smaller than _moeo2 on the first objective, then on the second, and so on
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
return _moeo1.objectiveVector() < _moeo2.objectiveVector();
}
};
/**
* Functor allowing to compare two solutions according to their fitness values
*/
template < class MOEOT >
class moeoFitnessComparator : public moeoComparator < MOEOT >
{
public:
/**
* Returns true if the fitness value of _moeo1 is smaller than the fitness value of _moeo2
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
return _moeo1.fitness() < _moeo2.fitness();
}
};
/**
* Functor allowing to compare two solutions according to their diversity values
*/
template < class MOEOT >
class moeoDiversityComparator : public moeoComparator < MOEOT >
{
public:
/**
* Returns true if the diversity value of _moeo1 is smaller than the diversity value of _moeo2
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
return _moeo1.diversity() < _moeo2.diversity();
}
};
/**
* Functor allowing to compare two solutions according to their fitness values, then according to their diversity values
*/
template < class MOEOT >
class moeoFitnessThenDiversityComparator : public moeoComparator < MOEOT >
{
public:
/**
* Returns true if _moeo1 is smaller than _moeo2 according to their fitness values, then according to their diversity values
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
if (_moeo1.fitness() == _moeo2.fitness())
{
return _moeo1.diversity() < _moeo2.diversity();
}
else
{
return _moeo1.fitness() < _moeo2.fitness();
}
}
};
/**
* Functor allowing to compare two solutions according to their diversity values, then according to their fitness values
*/
template < class MOEOT >
class moeoDiversityThenFitnessComparator : public moeoComparator < MOEOT >
{
public:
/**
* Returns true if _moeo1 is smaller than _moeo2 according to their diversity values, then according to their fitness values
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
if (_moeo1.diversity() == _moeo2.diversity())
{
return _moeo1.fitness() < _moeo2.fitness();
}
else
{
return _moeo1.diversity() < _moeo2.diversity();
}
}
};
/**
* Functor allowing to compare two solutions according to Pareto dominance relation => USEFULL ???
*
template < class MOEOT >
class moeoParetoDominanceComparator : public moeoComparator < MOEOT >
{
public:
/**
* Returns true if _moeo1 is dominated by _moeo2 according to Pareto dominance relation
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*
const bool operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
bool result = false;
typedef typename MOEOT::ObjectiveVector::Traits ObjectiveVectorTraits;
for (unsigned i=0; i<ObjectiveVectorTraits::nObjectives(); i++)
{
// first, we have to check if the 2 objective values are not equal on the ith objective
if ( fabs(_moeo1.objectiveVector()[i] - _moeo2.objectiveVector()[i]) > ObjectiveVectorTraits::tolerance() )
{
// if the ith objective have to be minimized...
if (ObjectiveVectorTraits::minimizing(i))
{
if (_moeo1.objectiveVector()[i] < _moeo2.objectiveVector()[i])
{
return false; // _moeo2 cannot dominate _moeo1
}
result = true;
}
// if the ith objective have to be maximized...
else if (ObjectiveVectorTraits::maximizing(i))
{
if (_moeo1.objectiveVector()[i] > _moeo2.objectiveVector()[i])
{
return false; // _moeo2 cannot dominate _moeo1
}
result = true;
}
}
}
return result;
}
};
*/
#endif /*MOEOPOPSORTER_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoDiversityAssignment.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEODIVERSITYASSIGNMENT_H_
#define MOEODIVERSITYASSIGNMENT_H_
#include <eoFunctor.h>
#include <eoPop.h>
/**
* Functor that sets the diversity values of a whole population
*/
template < class MOEOT >
class moeoDiversityAssignment : public eoUF < eoPop < MOEOT > &, void >
{};
#endif /*MOEODIVERSITYASSIGNMENT_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoEA.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOEA_H_
#define MOEOEA_H_
#include <eoAlgo.h>
/**
* Abstract class for multi-objective evolutionary algorithms
*/
template < class MOEOT >
class moeoEA : public eoAlgo < MOEOT > {};
#endif /*MOEOEA_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoEvalFunc.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOEVALFUNC_H_
#define MOEOEVALFUNC_H_
#include <eoEvalFunc.h>
/*
* Functor that evaluates one MOEO by setting all its objective values.
*/
template < class MOEOT >
class moeoEvalFunc : public eoEvalFunc< MOEOT > {};
#endif /*MOEOEVALFUNC_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoFastNonDominatedSortingFitnessAssignment.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOFASTNONDOMINATEDSORTINGFITNESSASSIGNMENT_H_
#define MOEOFASTNONDOMINATEDSORTINGFITNESSASSIGNMENT_H_
#include <eoPop.h>
#include <moeoFitnessAssignment.h>
#include <moeoComparator.h>
#include <moeoObjectiveVectorComparator.h>
/**
* Fitness assignment sheme based on Pareto-dominance count proposed in
* N. Srinivas, K. Deb, "Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms", Evolutionary Computation vol. 2, no. 3, pp. 221-248 (1994)
* and in
* K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, "A Fast and Elitist Multi-Objective Genetic Algorithm: NSGA-II", IEEE Transactions on Evolutionary Computation, vol. 6, no. 2 (2002).
* This strategy is, for instance, used in NSGA and NSGA-II.
*/
template < class MOEOT >
class moeoFastNonDominatedSortingFitnessAssignment : public moeoParetoBasedFitnessAssignment < MOEOT >
{
public:
/**
* Ctor
*/
moeoFastNonDominatedSortingFitnessAssignment() {}
/**
* Computes fitness values for every solution contained in the population _pop
* @param _pop the population
*/
void operator()(eoPop < MOEOT > & _pop)
{
// number of objectives for the problem under consideration
unsigned nObjectives = MOEOT::ObjectiveVector::nObjectives();
if (nObjectives == 1)
{
// one objective
oneObjective(_pop);
}
else if (nObjectives == 2)
{
// two objectives (the two objectives function is still to do)
mObjectives(_pop);
}
else if (nObjectives > 2)
{
// more than two objectives
mObjectives(_pop);
}
else
{
// problem with the number of objectives
throw std::runtime_error("Problem with the number of objectives in moeoFastNonDominatedSortingFitnessAssignment");
}
}
private:
/** the objective vector type of the solutions */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/** Functor to compare two objective vectors according to Pareto dominance relation */
moeoParetoObjectiveVectorComparator < ObjectiveVector > comparator;
/** Functor to compare two solutions on the first objective, then on the second, and so on */
moeoObjectiveComparator < MOEOT > objComparator;
/**
* Sets the fitness values for mono-objective problems
* @param _pop the population
*/
void oneObjective (eoPop < MOEOT > & _pop)
{
std::sort(_pop.begin(), _pop.end(), objComparator);
for (unsigned i=0; i<_pop.size(); i++)
{
_pop[i].fitness(i+1);
}
}
/**
* Sets the fitness values for bi-objective problems with a complexity of O(n log n), where n stands for the population size
* @param _pop the population
*/
void twoObjectives (eoPop < MOEOT > & _pop)
{
//... TO DO !
}
/**
* Sets the fitness values for problems with more than two objectives with a complexity of O(n² log n), where n stands for the population size
* @param _pop the population
*/
void mObjectives (eoPop < MOEOT > & _pop)
{
// S[i] = indexes of the individuals dominated by _pop[i]
std::vector < std::vector<unsigned> > S(_pop.size());
// n[i] = number of individuals that dominate the individual _pop[i]
std::vector < unsigned > n(_pop.size(), 0);
// fronts: F[i] = indexes of the individuals contained in the ith front
std::vector < std::vector<unsigned> > F(_pop.size()+1);
// used to store the number of the first front
F[1].reserve(_pop.size());
// flag to comparae solutions
int comparatorFlag;
for (unsigned p=0; p<_pop.size(); p++)
{
for (unsigned q=0; q<_pop.size(); q++)
{
// comparison of the 2 solutions according to Pareto dominance
comparatorFlag = comparator(_pop[p].objectiveVector(), _pop[q].objectiveVector());
// if p dominates q
if (comparatorFlag == 1)
{
// add q to the set of solutions dominated by p
S[p].push_back(q);
}
// if q dominates p
else if (comparatorFlag == -1)
{
// increment the domination counter of p
n[p]++;
}
}
// if no individual dominates p
if (n[p] == 0)
{
// p belongs to the first front
_pop[p].fitness(1);
F[1].push_back(p);
}
}
// front counter
unsigned counter=1;
unsigned p,q;
while (! F[counter].empty())
{
// used to store the number of the next front
F[counter+1].reserve(_pop.size());
for (unsigned i=0; i<F[counter].size(); i++)
{
p = F[counter][i];
for (unsigned j=0; j<S[p].size(); j++)
{
q = S[p][j];
n[q]--;
// if no individual dominates q anymore
if (n[q] == 0)
{
// q belongs to the next front
_pop[q].fitness(counter+1);
F[counter+1].push_back(q);
}
}
}
counter++;
}
}
};
#endif /*MOEOFASTNONDOMINATEDSORTINGFITNESSASSIGNMENT_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoFitnessAssignment.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOFITNESSASSIGNMENT_H_
#define MOEOFITNESSASSIGNMENT_H_
#include <eoFunctor.h>
#include <eoPop.h>
/**
* Functor that sets the fitness values of a whole population
*/
template < class MOEOT >
class moeoFitnessAssignment : public eoUF < eoPop < MOEOT > &, void >
{};
/**
* moeoScalarFitnessAssignment is a moeoFitnessAssignment for scalar strategies
*/
template < class MOEOT >
class moeoScalarFitnessAssignment : public moeoFitnessAssignment < MOEOT >
{};
/**
* moeoCriterionBasedFitnessAssignment is a moeoFitnessAssignment for criterion-based strategies
*/
template < class MOEOT >
class moeoCriterionBasedFitnessAssignment : public moeoFitnessAssignment < MOEOT >
{};
/**
* moeoParetoBasedFitnessAssignment is a moeoFitnessAssignment for Pareto-based strategies
*/
template < class MOEOT >
class moeoParetoBasedFitnessAssignment : public moeoFitnessAssignment < MOEOT >
{};
#endif /*MOEOFITNESSASSIGNMENT_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoGenerationalReplacement.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOGENERATIONALREPLACEMENT_H_
#define MOEOGENERATIONALREPLACEMENT_H_
#include <eoGenerationalReplacement.h>
#include <moeoGenerationalReplacement.h>
/**
* Generational replacement: only the new individuals are preserved
*/
template < class MOEOT >
class moeoGenerationalReplacement : public moeoReplacement < MOEOT >, public eoGenerationalReplacement < MOEOT > {};
#endif /*MOEOGENERATIONALREPLACEMENT_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoHybridLS.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOHYBRIDLS_H_
#define MOEOHYBRIDLS_H_
#include <eoContinue.h>
#include <eoPop.h>
#include <eoUpdater.h>
#include <eoSelect.h>
#include <moeoArchive.h>
#include <moeoLS.h>
/**
* This class allows to apply a multi-objective local search to a number of selected individuals contained in the archive
* at every generation until a stopping criteria is verified.
*/
template < class MOEOT >
class moeoHybridLS : public eoUpdater
{
public:
/**
* Ctor
* @param _term stopping criteria
* @param _select selector
* @param _ls a multi-objective local search
* @param _arch the archive
*/
eoHybridLS (eoContinue < MOEOT > & _term, eoSelect < MOEOT > & _select, moeoLS < MOEOT > & _ls, moeoArchive < MOEOT > & _arch) : term(_term), select(_select), ls(_ls), arch(_arch)
{}
/**
* Applies the multi-objective local search to selected individuals contained in the archive if the stopping criteria is not verified
*/
void operator () ()
{
if (! cont (arch))
{
// selection of solutions
eoPop < MOEOT > selectedSolutions;
select(arch, selectedSolutions);
// apply the local search to every selected solution
for (unsigned i=0; i<selectedSolutions.size(); i ++)
{
ls(selectedSolutions[i], arch);
}
}
}
private:
/** stopping criteria*/
eoContinue < MOEOT > & term;
/** selector */
eoSelect < MOEOT > & select;
/** multi-objective local search */
moeoLS < MOEOT > & ls;
/** archive */
moeoArchive < MOEOT > & arch;
};
#endif /*MOEOHYBRIDLS_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoLS.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOLS_H_
#define MOEOLS_H_
#include <eoFunctor.h>
#include <moeoArchive.h>
/**
* Abstract class for local searches applied to multi-objective optimization.
* Starting from only one solution, it produces a set of new non-dominated solutions.
*/
template < class MOEOT >
class moeoLS: public eoBF < const MOEOT &, moeoArchive < MOEOT > &, void >
{};
#endif /*MOEOLS_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoObjectiveVector.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOOBJECTIVEVECTOR_H_
#define MOEOOBJECTIVEVECTOR_H_
#include <iostream>
#include <math.h>
#include <vector>
#include <moeoObjectiveVectorComparator.h>
/**
* Abstract class allowing to represent a solution in the objective space (phenotypic representation).
* The template argument ObjectiveVectorTraits defaults to moeoObjectiveVectorTraits,
* but it can be replaced at will by any other class that implements the static functions defined therein.
* Some static funtions to access to the traits characteristics are re-defined in order not to write a lot of typedef's.
*/
template < class ObjectiveVectorTraits >
class moeoObjectiveVector
{
public:
/** The traits of objective vectors */
typedef ObjectiveVectorTraits Traits;
/**
* Parameters setting (for the objective vector of any solution)
* @param _nObjectives the number of objectives
* @param _bObjectives the min/max vector (true = min / false = max)
*/
static void setup(unsigned _nObjectives, std::vector < bool > & _bObjectives)
{
ObjectiveVectorTraits::setup(_nObjectives, _bObjectives);
}
/**
* Returns the number of objectives
*/
static unsigned nObjectives()
{
return ObjectiveVectorTraits::nObjectives();
}
/**
* Returns true if the _ith objective have to be minimized
* @param _i the index
*/
static bool minimizing(unsigned _i) {
return ObjectiveVectorTraits::minimizing(_i);
}
/**
* Returns true if the _ith objective have to be maximized
* @param _i the index
*/
static bool maximizing(unsigned _i) {
return ObjectiveVectorTraits::maximizing(_i);
}
};
/**
* This class allows to represent a solution in the objective space (phenotypic representation) by a std::vector of doubles,
* i.e. that an objective value is represented using a double, and this for any objective.
*/
template < class ObjectiveVectorTraits >
class moeoObjectiveVectorDouble : public moeoObjectiveVector < ObjectiveVectorTraits >, public std::vector < double >
{
public:
using std::vector< double >::size;
using std::vector< double >::operator[];
/**
* Ctor
*/
moeoObjectiveVectorDouble() : std::vector < double > (ObjectiveVectorTraits::nObjectives(), 0.0) {}
/**
* Ctor from a vector of doubles
* @param _v the std::vector < double >
*/
moeoObjectiveVectorDouble(std::vector <double> & _v) : std::vector < double > (_v) {}
/**
* Returns true if the current objective vector dominates _other according to the Pareto dominance relation
* (but it's better to use a moeoObjectiveVectorComparator object to compare solutions)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool dominates(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
moeoParetoObjectiveVectorComparator < moeoObjectiveVectorDouble<ObjectiveVectorTraits> > comparator;
return comparator(*this, _other)==1;
}
/**
* Returns true if the current objective vector is equal to _other (according to a tolerance value)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator==(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
for (unsigned i=0; i < size(); i++)
{
if ( fabs(operator[](i) - _other[i]) > ObjectiveVectorTraits::tolerance() )
{
return false;
}
}
return true;
}
/**
* Returns true if the current objective vector is different than _other (according to a tolerance value)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator!=(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
return ! operator==(_other);
}
/**
* Returns true if the current objective vector is smaller than _other on the first objective, then on the second, and so on
* (can be usefull for sorting/printing)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator<(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
for (unsigned i=0; i < size(); i++)
{
if ( fabs(operator[](i) - _other[i]) > ObjectiveVectorTraits::tolerance() )
{
if (operator[](i) < _other[i])
{
return true;
}
else
{
return false;
}
}
}
return false;
}
/**
* Returns true if the current objective vector is greater than _other on the first objective, then on the second, and so on
* (can be usefull for sorting/printing)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator>(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
return _other < *this;
}
/**
* Returns true if the current objective vector is smaller than or equal to _other on the first objective, then on the second, and so on
* (can be usefull for sorting/printing)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator<=(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
return operator==(_other) || operator<(_other);
}
/**
* Returns true if the current objective vector is greater than or equal to _other on the first objective, then on the second, and so on
* (can be usefull for sorting/printing)
* @param _other the other moeoObjectiveVectorDouble object to compare with
*/
bool operator>=(const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _other) const
{
return operator==(_other) || operator>(_other);
}
};
/**
* Output for a moeoObjectiveVectorDouble object
* @param _os output stream
* @param _objectiveVector the objective vector to write
*/
template < class ObjectiveVectorTraits >
std::ostream & operator<<(std::ostream & _os, const moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _objectiveVector)
{
for (unsigned i=0; i<_objectiveVector.size(); i++)
{
_os << _objectiveVector[i] << ' ';
}
return _os;
}
/**
* Input for a moeoObjectiveVectorDouble object
* @param _is input stream
* @param _objectiveVector the objective vector to read
*/
template < class ObjectiveVectorTraits >
std::istream & operator>>(std::istream & _is, moeoObjectiveVectorDouble < ObjectiveVectorTraits > & _objectiveVector)
{
_objectiveVector = moeoObjectiveVectorDouble < ObjectiveVectorTraits > ();
for (unsigned i=0; i<_objectiveVector.size(); i++)
{
_is >> _objectiveVector[i];
}
return _is;
}
#endif /*MOEOOBJECTIVEVECTOR_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoObjectiveVectorComparator.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOOBJECTIVEVECTORCOMPARATOR_H_
#define MOEOOBJECTIVEVECTORCOMPARATOR_H_
#include <math.h>
#include <eoFunctor.h>
/**
* Abstract class allowing to compare 2 objective vectors.
* The template argument ObjectiveVector have to be a moeoObjectiveVector.
*/
template < class ObjectiveVector >
class moeoObjectiveVectorComparator : public eoBF < const ObjectiveVector &, const ObjectiveVector &, int >
{};
/**
* This functor class allows to compare 2 objective vectors according to Pareto dominance
*/
template < class ObjectiveVector >
class moeoParetoObjectiveVectorComparator : public moeoObjectiveVectorComparator < ObjectiveVector >
{
public:
/**
* Returns 1 if _objectiveVector1 dominates _objectiveVector2, -1 if _objectiveVector2 dominates _objectiveVector1 and 0 if no one dominates the other
* @param _objectiveVector1 the first objective vector
* @param _objectiveVector2 the second objective vector
*/
int operator()(const ObjectiveVector & _objectiveVector1, const ObjectiveVector & _objectiveVector2)
{
bool dom1 = false;
bool dom2 = false;
for (unsigned i=0; i<ObjectiveVector::nObjectives(); i++)
{
// first, we have to check if the 2 objective values are not equal for the ith objective
if ( fabs(_objectiveVector1[i] - _objectiveVector2[i]) > ObjectiveVector::Traits::tolerance() )
{
// if the ith objective have to be minimized...
if (ObjectiveVector::minimizing(i))
{
if (_objectiveVector1[i] > _objectiveVector2[i])
{
dom2 = true; //_objectiveVector2[i] is better than _objectiveVector1[i]
}
else // _objectiveVector1[i] < _objectiveVector2[i]
{
dom1 = true; //_objectiveVector1[i] is better than _objectiveVector2[i]
}
}
// if the ith objective have to be maximized...
else if (ObjectiveVector::maximizing(i))
{
if (_objectiveVector1[i] > _objectiveVector2[i])
{
dom1 = true; //_objectiveVector1[i] is better than _objectiveVector2[i]
}
else // _objectiveVector1[i] < _objectiveVector2[i]
{
dom2 = true; //_objectiveVector2[i] is better than _objectiveVector1[i]
}
}
}
}
if (dom1 == dom2)
{
return 0; // no one dominates the other
}
if (dom1)
{
return 1; //_objectiveVector1 dominates _objectiveVector2
}
return -1; //_objectiveVector2 dominates _objectiveVector1
}
};
#endif /*MOEOOBJECTIVEVECTORCOMPARATOR_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoObjectiveVectorTraits.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOOBJECTIVEVECTORTRAITS_H_
#define MOEOOBJECTIVEVECTORTRAITS_H_
#include <vector>
#include <iostream>
#include <stdexcept>
/**
* A traits class for moeoObjectiveVector to specify the number of objectives and which ones have to be minimized or maximized
*/
class moeoObjectiveVectorTraits
{
public:
/** The tolerance value (used to compare solutions) */
const static double tol = 1e-6;
/**
* Parameters setting
* @param _nObjectives the number of objectives
* @param _bObjectives the min/max vector (true = min / false = max)
*/
static void setup(unsigned _nObjectives, std::vector < bool > & _bObjectives)
{
// in case the number of objectives was already set to a different value
if ( nObj && (nObj != _nObjectives) ) {
std::cout << "WARNING\n";
std::cout << "WARNING : the number of objectives are changing\n";
std::cout << "ARNING : Make sure all existing objects are destroyed\n";
std::cout << "WARNING\n";
}
// number of objectives
nObj = _nObjectives;
// min/max vector
bObj = _bObjectives;
// in case the number of objectives and the min/max vector size don't match
if (nObj != bObj.size())
throw std::runtime_error("Number of objectives and min/max size don't match in moeoObjectiveVectorTraits::setup");
}
/**
* Returns the number of objectives
*/
static unsigned nObjectives()
{
// in case the number of objectives would not be assigned yet
if (! nObj)
throw std::runtime_error("Number of objectives not assigned in moeoObjectiveVectorTraits");
return nObj;
}
/**
* Returns true if the _ith objective have to be minimized
* @param _i the index
*/
static bool minimizing(unsigned _i)
{
// in case the min/max vector would not be assigned yet
if (! bObj[_i])
throw std::runtime_error("We don't know if the ith objective have to be minimized or maximized in moeoObjectiveVectorTraits");
// in case there would be a wrong index
if (_i >= bObj.size())
throw std::runtime_error("Wrong index in moeoObjectiveVectorTraits");
return bObj[_i];
}
/**
* Returns true if the _ith objective have to be maximized
* @param _i the index
*/
static bool maximizing(unsigned _i) {
return (! minimizing(_i));
}
/**
* Returns the tolerance value (to compare solutions)
*/
static double tolerance()
{
return tol;
}
private:
/** The number of objectives */
static unsigned nObj;
/** The min/max vector */
static std::vector < bool > bObj;
};
#endif /*MOEOOBJECTIVEVECTORTRAITS_H_*/
// The static variables of the moeoObjectiveVectorTraits class need to be allocated
// (maybe it would have been better to put this on a moeoObjectiveVectorTraits.cpp file)
unsigned moeoObjectiveVectorTraits::nObj;
std::vector < bool > moeoObjectiveVectorTraits::bObj;

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoRandomSelectOne.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEORANDOMSELECTONE_H_
#define MOEORANDOMSELECTONE_H_
#include <moeoSelectOne.h>
#include <eoRandomSelect.h>
/**
* Selection strategy that selects only one element randomly from a whole population
*/
template < class MOEOT >
class moeoRandomSelectOne : public moeoSelectOne < MOEOT >, public eoRandomSelect < MOEOT > {};
#endif /*MOEORANDOMSELECTONE_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoReplacement.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOREPLACEMENT_H_
#define MOEOREPLACEMENT_H_
#include <eoReplacement.h>
/**
* Replacement strategy for multi-objective optimization
*/
template < class MOEOT >
class moeoReplacement : public eoReplacement < MOEOT > {};
#endif /*MOEOREPLACEMENT_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoSelectOne.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOSELECTONE_H_
#define MOEOSELECTONE_H_
#include <eoSelectOne.h>
/**
* Selection strategy for multi-objective optimization that selects only one element from a whole population
*/
template < class MOEOT >
class moeoSelectOne : public eoSelectOne < MOEOT > {};
#endif /*MOEOSELECTONE_H_*/

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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoSelectOneFormPopAndArch.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOSELECTONEFROMPOPANDARCH_H_
#define MOEOSELECTONEFROMPOPANDARCH_H_
#include <eoPop.h>
#include <utils/eoRNG.h>
#include <moeoArchive.h>
#include <moeoSelectOne.h>
#include <moeoRandomSelectOne.h>
/**
* Elitist selection process that consists in choosing individuals in the archive as well as in the current population.
*/
template<class EOT>
class moeoSelectOneFromPopAndArch : public moeoSelectOne<EOT>
{
public:
/**
* Ctor
* @param _popSelectOne the population's selection operator
* @param _archSelectOne the archive's selection operator
* @param _arch the archive
* @param _ratioFromPop the ratio of selected individuals from the population
*/
moeoSelectOneFromPopAndArch (moeoSelectOne<EOT> & _popSelectOne, moeoSelectOne<EOT> _archSelectOne, moeoArchive <EOT> & _arch, double _ratioFromPop=0.5)
: popSelectOne(_popSelectOne), archSelectOne(_archSelectOne), arch(_arch), ratioFromPop(_ratioFromPop)
{}
/**
* Ctor - the archive's selection operator is a random selector
* @param _popSelectOne the population's selection operator
* @param _arch the archive
* @param _ratioFromPop the ratio of selected individuals from the population
*/
moeoSelectOneFromPopAndArch (moeoSelectOne<EOT> & _popSelectOne, moeoArchive <EOT> & _arch, double _ratioFromPop=0.5)
: popSelectOne(_popSelectOne), archSelectOne(randomSelectOne), arch(_arch), ratioFromPop(_ratioFromPop)
{}
/**
* The selection process
*/
virtual const EOT & operator () (const eoPop<EOT> & pop) {
if (arch.size() > 0)
if (rng.flip(ratioFromPop))
return popSelectOne(pop);
else
return archSelectOne(arch);
else
return popSelectOne(pop);
}
/**
* Setups some population stats
*/
virtual void setup (const eoPop<EOT> & _pop) {
popSelectOne.setup(_pop);
}
private:
/** The population's selection operator */
moeoSelectOne<EOT> & popSelectOne;
/** The archive's selection operator */
moeoSelectOne<EOT> & archSelectOne;
/** The archive */
moeoArchive <EOT> & arch;
/** The ratio of selected individuals from the population*/
double ratioFromPop;
/** A random selection operator */
moeoRandomSelectOne<EOT> randomSelectOne;
};
#endif /*MOEOSELECTONEFROMPOPANDARCH_H_*/

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SUBDIRS=lesson1

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###### General ######
# --help=0 # -h : Prints this message
# --stopOnUnknownParam=1 # Stop if unkown param entered
# --seed=1165485212 # -S : Random number seed
###### Evolution Engine ######
--popSize=20 # -P : Population Size
--selCrit=NSGA-II # -S : Multi-objective selection criterion: NSGA, NSGA-II, IBEA, ParetoRanking, ParetoSharing
--nicheSize=1 # -n : Size of niche for NSGA-I or ParetoSharing
--kappa=0.05 # -k : Scaling factor kappa for IBEA
--indicator=Epsilon # -I : Binary quality indicator for IBEA : Epsilon, Hypervolume
--rho=1.1 # -r : reference point for the hypervolume calculation (must not be smaller than 1)
--selection=DetTour(2) # -s : Selection: Roulette, DetTour(T), StochTour(t) or Random
--elitism=0 # -E : Use elitism in the selection process (individuals from the archive are randomly selected)
--ratio=0.8 # Ratio from the population for elitism (must not be greater than 1)
--nbOffspring=100% # -O : Nb of offspring (percentage or absolute)
--replacement=Plus # -R : Replacement: Plus, DistinctPlus or Generational
###### Output ######
--useEval=1 # Use nb of eval. as counter (vs nb of gen.)
--printPop=0 # Print sorted pop. every gen.
###### Output - Disk ######
--resDir=Res # Directory to store DISK outputs
--eraseDir=1 # erase files in dirName if any
--frontFileFrequency=1(0,1) # File save frequency in objective spaces (std::pairs of comma-separated objectives in 1 single parentheses std::pair)
###### Output - Graphical ######
--plotFront=0 # Objective plots (requires corresponding files - see frontFileFrequency
###### Persistence ######
# --Load= # -L : A save file to restart from
--recomputeFitness=0 # -r : Recompute the fitness after re-loading the pop.?
--saveFrequency=0 # Save every F generation (0 = only final state, absent = never)
--saveTimeInterval=0 # Save every T seconds (0 or absent = never)
--status=./FlowShopEA.status # Status file
###### Representation ######
--BenchmarkFile=benchmarks/020_05_01.txt # -B : Benchmark file name (benchmarks are available at www.lifl.fr/~basseur/BenchsUncertain/) REQUIRED
###### Stopping criterion ######
--maxGen=100 # -G : Maximum number of generations () = none)
--CtrlC=1 # -C : Terminate current generation upon Ctrl C
###### Variation Operators ######
--crossRate=1 # Relative rate for the only crossover
--shiftMutRate=0.5 # Relative rate for shift mutation
--exchangeMutRate=0.5 # Relative rate for exchange mutation
--pCross=0.25 # -c : Probability of Crossover
--pMut=0.35 # -m : Probability of Mutation

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noinst_PROGRAMS = FlowShopEA
FlowShopEA_SOURCES = FlowShopEA.cpp
LDADD = -L$(top_builddir)/src ${EO_DIR}/src/libeo.a ${EO_DIR}/src/utils/libeoutils.a
INCLUDES = -I${EO_DIR}/src/ -I$(top_srcdir)/src

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20
5
873654221
0
468
54 79 16 66 58
1
325
83 3 89 58 56
2
923
15 11 49 31 20
3
513
71 99 15 68 85
4
1070
77 56 89 78 53
5
690
36 70 45 91 35
6
602
53 99 60 13 53
7
289
38 60 23 59 41
8
873
27 5 57 49 69
9
342
87 56 64 85 13
10
764
76 3 7 85 86
11
268
91 61 1 9 72
12
1158
14 73 63 39 8
13
646
29 75 41 41 49
14
1111
12 47 63 56 47
15
965
77 14 47 40 87
16
703
32 21 26 54 58
17
1205
87 86 75 77 18
18
334
68 5 77 51 68
19
1111
94 77 40 31 28

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@ -0,0 +1,63 @@
20
5
379008056
0
517
26 59 78 88 69
1
461
38 62 90 54 30
2
832
27 44 64 47 61
3
653
88 10 49 83 35
4
933
95 23 47 84 53
5
811
55 64 20 9 98
6
966
54 47 61 30 94
7
448
63 68 93 11 33
8
577
23 54 36 92 77
9
1122
45 9 47 63 31
10
666
86 30 70 62 54
11
1189
43 31 54 75 71
12
470
43 92 87 48 78
13
475
40 7 13 23 9
14
462
37 14 40 85 79
15
866
54 95 34 23 51
16
392
35 76 55 4 76
17
310
59 82 13 31 56
18
719
43 91 11 13 80
19
1221
50 37 5 98 72

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@ -0,0 +1,63 @@
20
10
587595453
0
1250
74 28 89 60 54 92 9 4 25 15
1
1371
21 3 52 88 66 11 8 18 15 84
2
637
58 27 56 26 12 54 88 25 91 8
3
616
4 61 13 58 57 97 72 28 49 30
4
917
21 34 7 76 70 57 27 95 56 95
5
937
28 76 32 98 82 53 22 51 10 79
6
1435
58 64 32 29 99 65 50 84 62 9
7
1197
83 87 98 47 84 77 2 18 70 91
8
1301
31 54 46 79 16 51 49 6 76 76
9
637
61 98 60 26 41 36 82 90 99 26
10
749
94 76 23 19 23 53 93 69 58 42
11
1223
44 41 87 48 11 19 96 61 83 66
12
887
97 70 7 95 68 54 43 57 84 70
13
1316
94 43 36 78 58 86 13 5 64 91
14
1330
66 42 26 77 30 40 60 75 74 67
15
1380
6 79 85 90 5 56 11 4 14 3
16
767
37 88 7 24 5 79 37 38 18 98
17
574
22 15 34 10 39 74 91 28 48 4
18
1398
99 49 36 85 58 24 84 4 96 71
19
1179
83 72 48 55 31 3 67 80 86 62

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@ -0,0 +1,63 @@
20
10
1401007982
0
1279
80 59 59 31 30 53 93 90 65 64
1
1481
13 83 70 64 88 19 79 92 97 38
2
1157
64 85 76 11 14 99 88 35 27 44
3
1391
77 85 10 9 22 62 77 13 25 46
4
763
17 70 65 32 93 88 94 75 61 66
5
1456
78 35 19 58 48 93 39 55 24 31
6
900
82 2 77 98 10 34 74 80 97 48
7
1047
4 76 86 95 7 72 46 67 61 27
8
1355
72 46 21 25 14 42 17 3 75 82
9
1262
93 72 75 4 91 65 30 93 92 51
10
1329
68 69 96 45 5 39 62 54 73 90
11
562
25 46 3 60 43 79 77 67 21 63
12
684
67 3 50 87 30 9 43 25 29 85
13
567
80 57 57 31 79 26 98 77 3 36
14
765
43 71 66 1 39 72 48 38 96 69
15
808
93 77 84 96 34 29 14 98 51 67
16
999
21 33 98 22 77 36 45 96 26 81
17
548
33 49 55 95 81 48 25 20 44 18
18
577
14 59 70 73 11 57 98 15 56 81
19
704
30 82 32 77 10 95 30 36 31 72

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@ -0,0 +1,63 @@
20
20
479340445
0
1696
50 78 36 85 9 75 46 73 71 7 49 3 60 12 75 31 70 20 88 9
1
1273
90 56 43 88 92 64 94 3 49 40 49 53 88 47 19 61 78 78 30 41
2
1546
39 9 10 60 98 96 6 56 36 33 15 59 15 46 60 47 41 38 34 22
3
1882
34 43 19 98 44 95 19 73 87 64 18 7 26 17 87 32 9 26 33 34
4
1117
66 84 55 4 51 22 20 80 8 5 65 65 11 43 27 34 47 64 21 83
5
1181
81 73 48 99 8 41 51 82 25 25 55 58 16 16 48 69 94 62 7 55
6
1416
27 66 85 53 31 26 85 36 76 89 1 24 55 91 72 32 26 11 94 3
7
1635
48 38 70 21 15 33 92 98 73 95 79 55 59 94 88 1 65 38 10 8
8
1723
46 83 82 33 47 68 43 90 80 58 10 26 81 73 48 1 17 68 73 75
9
1932
68 57 39 53 31 9 75 46 6 83 37 40 53 89 59 80 42 37 85 30
10
1219
48 97 91 63 80 81 70 10 6 28 77 89 92 12 74 19 59 74 82 57
11
1521
92 52 82 18 83 28 70 46 33 35 80 94 23 58 86 57 80 9 62 65
12
1322
78 77 85 45 20 61 36 65 79 74 79 51 55 25 49 98 7 65 99 89
13
1057
84 13 17 29 84 69 31 83 10 5 84 74 79 24 94 37 75 16 67 60
14
1922
93 12 6 43 69 37 76 75 93 6 93 54 13 55 15 31 63 38 61 90
15
1130
39 2 54 41 49 57 63 47 65 9 21 86 89 1 95 51 96 85 10 84
16
1411
43 65 87 80 93 36 89 61 26 3 85 22 2 67 41 66 7 50 4 74
17
1840
1 93 85 4 39 80 46 28 73 2 64 83 17 3 94 38 10 62 70 17
18
1741
65 39 4 31 13 96 25 59 42 35 46 19 97 1 15 62 47 39 31 2
19
1377
87 1 72 19 88 74 88 22 18 41 35 44 41 71 71 72 38 97 49 19

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50
5
1328042058
0
1290
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1
2352
87 37 4 67 94
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362
13 25 92 4 9
3
305
11 95 92 14 57
4
262
41 49 72 93 29
5
1250
43 12 45 54 79
6
2170
93 59 5 21 55
7
1601
69 17 98 20 73
8
2039
80 46 93 6 65
9
1628
13 20 17 18 86
10
483
24 52 79 75 25
11
285
72 44 11 25 39
12
1092
38 92 16 16 76
13
936
81 75 89 77 24
14
2349
83 95 81 28 38
15
473
88 33 92 24 5
16
2325
26 10 45 15 91
17
747
6 45 61 77 29
18
970
89 2 39 36 22
19
434
67 62 28 16 27
20
1258
70 62 94 32 39
21
2405
30 82 87 46 31
22
862
89 29 23 21 46
23
298
30 29 1 81 18
24
2014
68 94 55 28 93
25
2608
21 20 91 70 58
26
1737
78 42 67 89 85
27
2214
46 80 91 54 58
28
1910
99 94 4 96 97
29
2245
10 35 60 62 10
30
2211
17 8 38 46 79
31
547
23 41 25 60 93
32
2237
83 65 90 19 2
33
1327
47 4 93 97 87
34
700
86 71 13 13 17
35
1011
18 30 65 7 18
36
2001
67 14 25 44 10
37
1230
46 32 34 7 50
38
1020
4 50 47 73 8
39
1918
14 30 98 15 26
40
1001
4 27 91 66 14
41
1383
20 98 11 70 21
42
1229
88 39 46 97 15
43
2594
50 84 50 33 10
44
403
84 65 77 97 85
45
1515
58 12 5 64 46
46
431
93 58 14 73 42
47
1971
76 45 47 28 18
48
939
50 49 80 4 36
49
2028
30 15 45 87 2

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50
10
1958948863
0
793
46 61 3 51 37 79 83 22 27 24
1
2280
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939
79 51 58 21 42 68 38 99 75 39
3
2591
45 25 85 57 47 75 38 25 94 66
4
1540
97 73 33 69 94 37 86 98 18 41
5
2386
10 93 71 51 14 44 67 55 41 46
6
812
44 28 58 50 94 34 23 80 37 24
7
2524
24 90 56 51 34 39 19 82 58 23
8
1370
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9
1319
75 59 43 19 36 62 78 68 20 50
10
2388
66 64 48 63 88 74 66 47 2 93
11
961
49 2 69 91 51 28 67 74 39 22
12
2831
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13
2790
61 35 35 6 71 43 23 61 81 81
14
2076
19 53 82 31 94 98 67 95 33 94
15
2519
47 40 53 63 99 83 8 55 14 97
16
1981
84 81 64 36 11 91 77 11 88 54
17
695
13 26 11 39 97 27 71 42 22 82
18
2133
11 85 61 57 44 6 85 72 36 11
19
1871
19 4 36 47 77 82 29 14 65 91
20
1495
98 4 53 56 69 60 49 8 79 23
21
754
2 10 87 65 91 44 3 98 23 32
22
783
85 63 88 59 38 43 94 90 66 26
23
984
44 96 10 4 25 76 76 36 5 22
24
2004
7 55 32 10 87 99 95 75 15 12
25
2269
73 71 38 12 7 66 48 69 51 23
26
1771
19 66 25 62 66 11 4 26 2 34
27
2030
69 94 24 43 54 35 37 24 81 87
28
2603
12 7 90 49 86 52 82 55 12 59
29
2150
73 15 7 54 49 8 57 98 40 2
30
2157
85 11 11 87 3 40 61 86 59 38
31
2187
23 99 49 29 48 62 6 30 32 84
32
937
53 37 2 2 44 25 97 92 16 62
33
728
16 50 76 18 93 24 5 94 87 10
34
510
88 56 17 75 37 30 27 66 78 11
35
2786
8 69 32 39 82 1 95 47 41 93
36
2134
26 22 39 77 31 73 46 3 43 57
37
1046
42 56 9 69 59 27 92 41 94 81
38
2849
58 67 83 15 78 16 46 41 1 10
39
1956
63 63 69 78 33 91 52 47 93 40
40
2456
7 96 67 68 36 33 8 89 22 62
41
1105
2 74 28 37 3 11 11 28 93 49
42
1560
44 4 88 22 58 99 7 39 62 90
43
1745
38 42 23 41 10 2 54 80 53 34
44
2216
24 40 91 92 98 60 72 47 30 11
45
1157
76 30 71 67 6 90 57 57 34 81
46
1317
85 93 3 24 44 36 85 74 27 51
47
2372
61 36 26 87 62 62 22 38 30 21
48
777
32 25 41 91 24 15 87 59 54 39
49
972
90 87 96 31 94 3 65 5 77 27

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50
20
1539989115
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2509
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2039
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2
3096
42 69 79 46 59 89 93 24 64 50 99 25 59 49 54 78 11 55 16 4
3
2950
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4
1249
44 53 46 76 21 47 8 48 17 66 88 38 22 65 84 53 87 85 14 62
5
2481
57 21 23 31 59 66 45 57 78 84 93 98 88 34 54 43 66 44 92 39
6
3193
89 10 40 36 78 76 37 78 82 98 34 96 35 10 2 85 98 47 67 97
7
3253
53 31 95 8 25 15 78 5 4 55 72 20 49 56 80 19 42 66 77 57
8
2123
84 80 87 37 30 18 26 50 72 70 42 15 78 51 84 48 23 19 46 9
9
2390
62 18 37 21 38 54 98 83 93 32 65 36 69 97 66 49 45 66 41 54
10
1764
91 5 24 3 78 24 17 70 68 31 39 65 76 52 25 66 52 61 78 13
11
2940
14 18 24 76 79 55 25 21 25 64 79 97 2 46 16 22 6 60 3 47
12
1635
95 17 65 67 58 96 21 71 67 11 9 27 14 16 79 37 3 98 72 6
13
3171
89 71 62 5 44 10 28 58 80 9 26 25 3 50 90 51 64 82 95 70
14
2670
4 90 19 47 38 12 68 36 43 32 72 61 22 96 51 82 55 79 53 19
15
2932
95 93 67 72 76 96 24 50 93 58 29 24 26 85 29 59 97 71 59 97
16
2054
2 14 66 66 70 53 62 31 21 98 36 97 44 61 29 88 83 28 34 41
17
3238
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18
2466
68 52 65 95 85 77 60 29 14 25 57 75 4 30 83 19 81 27 42 57
19
2384
20 7 59 49 8 6 64 30 30 4 95 92 16 90 83 32 92 33 63 60
20
3473
33 78 2 47 10 91 38 93 59 45 93 73 55 42 19 52 68 13 27 62
21
3290
51 57 67 26 84 14 90 49 83 60 79 21 43 88 95 9 46 9 92 14
22
2086
98 41 82 81 42 41 87 83 85 87 88 29 87 37 87 96 56 12 8 90
23
2560
8 75 90 56 67 30 1 89 85 31 77 3 35 43 12 23 88 51 65 76
24
3253
85 98 30 76 20 85 99 44 70 1 94 96 76 88 34 64 50 16 34 12
25
3205
86 93 63 66 24 17 34 38 35 96 39 51 98 91 23 22 13 49 6 89
26
2534
73 33 5 36 75 23 9 62 2 22 74 26 78 14 44 37 23 83 42 37
27
2039
4 75 93 53 23 60 22 45 76 95 46 44 81 63 30 3 13 48 39 35
28
2273
40 68 53 26 33 76 74 22 46 73 17 56 48 65 82 52 49 13 2 91
29
2062
98 33 85 52 60 39 14 85 72 77 30 31 25 74 83 44 18 78 7 69
30
1909
12 60 81 29 20 85 14 39 69 30 62 64 81 71 42 11 50 96 85 55
31
2432
59 82 73 36 75 10 84 98 46 88 77 38 27 8 56 21 94 77 32 48
32
2624
44 24 34 68 83 65 75 56 3 14 43 44 84 39 89 85 71 68 14 56
33
3325
46 99 74 21 26 15 37 68 57 22 98 46 59 95 38 6 64 88 74 84
34
3427
2 4 13 71 92 55 32 84 71 93 48 66 98 82 96 40 31 77 59 22
35
1318
41 97 78 61 29 41 29 77 77 48 14 31 14 17 10 68 21 76 95 51
36
1539
28 24 35 71 39 28 32 67 33 10 45 48 32 38 3 30 2 73 48 43
37
3223
83 50 20 69 14 93 89 53 49 7 25 27 95 69 53 35 63 92 37 50
38
1703
28 55 16 28 74 88 12 46 59 14 98 82 30 17 97 58 58 72 59 62
39
1051
21 91 48 86 66 27 47 24 82 91 30 51 13 24 11 31 36 87 4 61
40
1512
80 46 12 27 86 77 19 52 59 5 90 90 68 66 65 11 64 66 42 10
41
2589
71 58 11 41 10 81 97 96 70 43 92 63 19 75 47 11 52 98 93 87
42
3248
4 17 80 86 27 19 7 2 76 30 35 85 57 52 76 6 8 40 32 99
43
2047
60 47 9 55 8 76 12 88 10 79 13 36 65 59 22 59 94 31 30 40
44
3333
34 82 24 17 7 55 43 33 65 39 75 69 13 4 17 64 51 75 16 91
45
1760
55 6 76 62 97 67 89 27 19 34 55 67 63 73 14 65 36 45 95 64
46
2333
53 15 32 96 84 65 14 49 77 77 80 81 26 56 11 23 82 98 58 62
47
2400
96 91 35 59 56 8 33 78 86 81 67 18 96 19 69 80 30 90 12 53
48
2142
37 74 66 53 61 18 56 82 21 11 3 81 53 39 91 75 17 4 95 33
49
1231
37 42 48 93 9 56 57 65 75 10 93 72 94 51 53 63 21 23 21 16

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100
5
896678084
0
1682
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1
4503
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2
1249
57 97 38 46 34
3
4984
52 88 30 3 96
4
2923
66 52 20 22 79
5
2401
67 49 68 33 62
6
1978
33 88 4 90 6
7
5318
62 15 78 94 15
8
4769
65 55 41 98 94
9
2093
7 6 2 9 39
10
2438
6 77 62 84 85
11
3143
31 49 38 69 17
12
698
42 46 95 26 55
13
621
82 14 82 22 59
14
2463
48 35 96 49 48
15
3865
45 40 56 90 11
16
1563
79 1 61 81 63
17
1461
86 70 34 12 98
18
2285
10 46 1 54 33
19
4381
47 28 9 53 49
20
1057
67 73 57 18 41
21
3190
86 24 80 56 82
22
4493
64 44 58 43 12
23
4604
38 55 7 50 61
24
1592
13 94 56 82 94
25
4645
69 52 31 18 80
26
2729
4 40 92 89 84
27
1925
21 76 84 49 18
28
3843
25 92 25 20 68
29
4188
74 22 20 76 6
30
2635
11 46 65 90 98
31
3773
85 19 36 64 47
32
269
50 18 67 89 6
33
307
21 50 96 16 55
34
907
93 31 35 3 73
35
288
98 41 59 12 70
36
5211
91 51 76 45 56
37
331
26 73 66 67 46
38
1499
4 22 83 97 50
39
1119
28 21 37 80 90
40
4399
61 79 33 97 89
41
1306
8 93 2 92 88
42
1149
55 98 95 56 50
43
3919
68 89 20 50 99
44
3875
30 44 84 95 41
45
3485
26 64 43 25 36
46
2800
81 93 4 52 16
47
1893
95 66 44 21 84
48
2341
49 14 74 47 98
49
874
6 10 92 4 44
50
3355
82 36 55 67 42
51
345
71 36 98 62 43
52
1530
61 69 8 63 62
53
3516
84 79 30 25 49
54
3194
29 90 18 3 22
55
985
44 51 28 55 16
56
1638
83 81 54 87 14
57
2970
12 16 68 84 55
58
4265
54 28 42 28 45
59
3494
19 26 28 73 20
60
5134
52 97 12 8 35
61
3520
59 33 57 38 89
62
3570
74 77 81 80 7
63
1335
42 68 19 53 64
64
313
60 28 16 70 36
65
1031
43 46 88 9 5
66
4360
80 16 75 87 63
67
2814
34 96 11 33 8
68
571
74 59 57 11 76
69
538
46 56 99 65 95
70
2856
40 4 4 92 40
71
747
27 52 51 34 51
72
3321
79 89 26 64 98
73
612
1 84 6 96 77
74
4517
98 42 16 67 92
75
1532
44 37 71 54 35
76
2848
8 90 52 26 3
77
4701
55 51 96 32 56
78
263
55 84 89 10 1
79
5340
27 16 79 91 17
80
3979
69 39 91 90 70
81
4804
79 16 57 31 45
82
1574
97 37 2 7 87
83
3644
39 19 33 6 37
84
1512
54 15 42 77 70
85
4445
75 68 1 91 84
86
3253
88 7 40 42 69
87
5334
87 58 76 5 7
88
2338
97 47 85 46 5
89
1071
4 27 99 54 97
90
2398
79 82 65 56 47
91
1675
59 72 98 1 12
92
4974
7 1 78 24 54
93
1785
89 7 61 62 84
94
3391
61 22 83 47 49
95
4517
42 40 30 63 89
96
2909
79 59 14 39 86
97
2733
85 16 62 63 37
98
853
66 7 41 95 52
99
4261
99 72 91 45 85

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100
10
1539989115
0
3490
52 82 63 79 80 53 71 95 92 61
1
2540
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4675
42 79 59 93 64 99 59 54 11 16
3
4381
75 95 35 32 77 62 82 22 83 42
4
945
44 46 21 8 17 88 22 84 87 14
5
3435
57 23 59 45 78 93 88 54 66 92
6
4873
89 40 78 37 82 34 35 2 98 67
7
4993
53 95 25 78 4 72 49 80 42 77
8
2710
84 87 30 26 72 42 78 84 23 46
9
3251
62 37 38 98 93 65 69 66 45 41
10
1985
91 24 78 17 68 39 76 25 52 78
11
4361
14 24 79 25 25 79 2 16 6 3
12
1726
95 65 58 21 67 9 14 79 3 72
13
4828
89 62 44 28 80 26 3 90 64 95
14
3816
4 19 38 68 43 72 22 51 55 53
15
4345
95 67 76 24 93 29 26 29 97 59
16
2572
2 66 70 62 21 36 44 29 83 34
17
4963
97 6 72 89 33 48 1 90 42 66
18
3403
68 65 85 60 14 57 4 83 81 42
19
3238
20 59 8 64 30 95 16 83 92 63
20
5437
33 2 10 38 59 93 55 19 68 27
21
5068
51 67 84 90 83 79 43 95 46 92
22
2635
98 82 42 87 85 88 87 87 56 8
23
3593
8 90 67 1 85 77 35 12 88 65
24
4993
85 30 20 99 70 94 76 34 50 34
25
4897
86 63 24 34 35 39 98 23 13 6
26
3542
73 5 75 9 2 74 78 44 23 42
27
2541
4 93 23 22 76 46 81 30 13 39
28
3014
40 53 33 74 46 17 48 82 49 2
29
2587
98 85 60 14 72 30 25 83 18 7
30
2278
12 81 20 14 69 62 81 42 50 85
31
3336
59 73 75 84 46 77 27 56 94 32
32
3723
44 34 83 75 3 43 84 89 71 14
33
5138
46 74 26 37 57 98 59 38 64 74
34
5345
2 13 92 32 71 48 98 96 31 59
35
1084
41 78 29 29 77 14 14 10 21 95
36
1531
28 35 39 32 33 45 32 3 2 48
37
4932
83 20 14 89 49 25 95 53 63 37
38
1863
28 16 74 12 59 98 30 97 58 59
39
545
21 48 66 47 82 30 13 11 36 4
40
1477
80 12 86 19 59 90 68 65 64 42
41
3653
71 11 10 97 70 92 19 47 52 93
42
4983
4 80 27 7 76 35 57 76 8 32
43
2558
60 9 8 12 10 13 65 22 94 30
44
5156
34 24 7 43 65 75 13 17 51 16
45
1977
55 76 97 89 19 55 63 14 36 95
46
3136
53 32 84 14 77 80 26 11 82 58
47
3271
96 35 56 33 86 67 96 69 30 12
48
2748
37 66 61 56 21 3 53 91 17 95
49
909
37 48 9 57 75 93 94 53 21 21
50
4366
63 16 94 22 96 54 27 3 80 74
51
4943
99 26 34 6 3 67 93 80 38 38
52
4596
69 46 89 24 50 25 49 78 55 4
53
1793
70 66 62 55 57 77 63 32 34 31
54
4596
53 76 47 48 66 38 65 53 85 62
55
3717
21 31 66 57 84 98 34 43 44 39
56
4624
10 36 76 78 98 96 10 85 47 97
57
5212
31 8 15 5 55 20 56 19 66 57
58
5604
80 37 18 50 70 15 51 48 19 9
59
2110
18 21 54 83 32 36 97 49 66 54
60
2568
5 3 24 70 31 65 52 66 61 13
61
5330
18 76 55 21 64 97 46 22 60 47
62
676
17 67 96 71 11 27 16 37 98 6
63
1603
71 5 10 58 9 25 50 51 82 70
64
1085
90 47 12 36 32 61 96 82 79 19
65
5128
93 72 96 50 58 24 85 59 71 97
66
938
14 66 53 31 98 97 61 88 28 41
67
4778
49 56 92 86 95 61 76 77 74 1
68
1986
52 95 77 29 25 75 30 19 27 57
69
2115
7 49 6 30 4 92 90 32 33 60
70
616
78 47 91 93 45 73 42 52 13 62
71
534
57 26 14 49 60 21 88 9 9 14
72
1231
41 81 41 83 87 29 37 96 12 90
73
3376
75 56 30 89 31 3 43 23 51 76
74
2922
98 76 85 44 1 96 88 64 16 12
75
2152
93 66 17 38 96 51 91 22 49 89
76
1813
33 36 23 62 22 26 14 37 83 37
77
3561
75 53 60 45 95 44 63 3 48 35
78
4603
68 26 76 22 73 56 65 52 13 91
79
2813
33 52 39 85 77 31 74 44 78 69
80
528
60 29 85 39 30 64 71 11 96 55
81
1112
82 36 10 98 88 38 8 21 77 48
82
4387
24 68 65 56 14 44 39 85 68 56
83
4573
99 21 15 68 22 46 95 6 88 84
84
5585
4 71 55 84 93 66 82 40 77 22
85
2680
97 61 41 77 48 31 17 68 76 51
86
3262
24 71 28 67 10 48 38 30 73 43
87
3913
50 69 93 53 7 27 69 35 92 50
88
1749
55 28 88 46 14 82 17 58 72 62
89
2369
91 86 27 24 91 51 24 31 87 61
90
888
46 27 77 52 5 90 66 11 66 10
91
3107
58 41 81 96 43 63 75 11 98 87
92
4964
17 86 19 2 30 85 52 6 40 99
93
5249
47 55 76 88 79 36 59 59 31 40
94
5632
82 17 55 33 39 69 4 64 75 91
95
893
6 62 67 27 34 67 73 65 45 64
96
3432
15 96 65 49 77 81 56 23 98 62
97
5507
91 59 8 78 81 18 19 80 90 53
98
2007
74 53 18 82 11 81 39 75 4 33
99
5336
42 93 56 65 10 72 51 63 23 16

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100
20
450926852
0
1420
12 27 24 42 5 27 51 48 42 31 48 51 8 1 1 28 4 44 6 57
1
1890
72 97 57 16 42 69 9 44 18 49 92 84 37 77 59 81 40 6 49 88
2
5212
29 53 68 44 47 38 22 73 31 78 43 28 33 92 53 96 5 18 84 88
3
2835
16 16 58 75 47 66 15 95 18 23 35 63 4 57 22 99 37 51 72 43
4
4466
22 36 76 32 47 21 84 72 55 37 7 86 8 46 10 79 80 77 39 25
5
5004
61 28 70 66 78 65 38 12 82 34 51 99 38 75 48 97 46 47 51 81
6
1562
69 50 72 31 94 3 71 30 64 43 85 27 97 2 94 15 14 27 77 3
7
1927
71 41 56 6 18 7 11 22 36 7 66 24 75 14 46 6 81 17 59 3
8
2807
86 42 56 6 14 10 45 25 48 69 87 36 76 14 57 77 16 42 97 78
9
2057
16 86 55 52 97 11 48 92 74 97 71 83 93 79 55 98 10 84 5 97
10
5762
54 2 89 7 54 41 29 5 17 15 16 24 69 64 66 5 79 3 83 74
11
5182
53 45 23 92 73 64 31 44 60 38 40 54 10 8 69 51 35 69 51 71
12
5558
64 86 42 45 94 9 14 90 18 80 22 34 25 73 7 51 41 3 9 50
13
2591
96 43 26 70 17 15 56 35 88 78 12 49 40 15 13 60 83 6 9 70
14
4353
79 92 87 72 97 71 59 24 37 89 2 43 88 71 64 17 13 94 59 23
15
4442
68 73 17 48 7 86 35 64 29 95 90 5 90 6 83 98 93 58 30 43
16
2375
98 99 38 86 94 2 7 82 19 1 63 70 57 54 39 46 55 65 86 51
17
3311
87 84 24 63 94 26 20 7 51 18 52 56 39 59 46 87 48 36 49 97
18
2369
40 83 82 61 68 57 48 34 20 11 15 71 29 49 59 44 35 28 46 57
19
4728
74 61 55 92 4 78 88 91 7 11 6 12 97 38 36 18 75 68 13 77
20
5437
22 7 47 73 60 84 54 59 43 92 18 30 51 21 69 71 66 73 45 90
21
3616
23 8 7 49 70 20 30 5 77 99 87 77 97 60 47 93 82 81 51 58
22
4472
47 62 99 53 68 21 81 47 95 81 66 55 5 8 83 97 3 12 68 75
23
2738
55 3 89 20 22 3 2 96 92 79 7 92 75 35 25 44 79 89 82 4
24
1604
21 21 20 97 17 39 1 7 27 53 43 78 91 81 12 18 78 53 6 12
25
3121
90 50 65 58 59 64 78 53 70 47 27 79 80 96 28 59 48 14 99 2
26
2296
68 71 3 59 98 51 8 60 91 48 78 52 81 61 30 9 99 88 12 4
27
2107
14 95 45 29 55 83 8 77 74 32 80 19 60 89 49 45 91 78 8 28
28
5637
42 70 89 98 76 12 71 61 62 58 73 16 97 58 81 78 29 63 36 54
29
1686
41 60 96 61 3 16 60 14 80 33 86 21 14 32 56 67 87 81 24 39
30
2186
40 4 16 83 21 3 41 88 85 65 82 37 2 59 96 65 27 29 82 30
31
5311
63 58 42 8 10 1 39 97 8 86 33 85 55 89 89 50 2 15 73 71
32
3210
23 16 70 83 11 88 8 92 39 60 92 56 97 99 73 87 48 81 66 89
33
1223
75 30 69 73 44 80 96 65 85 47 8 29 60 7 52 29 33 84 69 33
34
2856
4 80 77 2 29 77 3 73 83 89 87 56 8 79 12 80 92 36 71 85
35
4618
31 71 46 56 43 2 79 19 76 40 64 23 30 38 98 14 15 8 70 2
36
1981
87 59 20 7 60 14 48 99 31 72 7 19 87 1 12 70 55 60 61 69
37
2755
25 75 71 15 14 60 23 92 12 54 26 52 42 67 40 10 24 24 42 20
38
1976
47 52 91 55 46 45 38 19 69 29 79 39 16 63 70 30 59 57 77 64
39
1153
70 25 8 3 3 39 85 66 26 57 49 4 56 42 35 19 41 87 10 94
40
5686
1 86 34 73 60 32 32 25 54 93 71 46 86 3 58 51 49 61 2 3
41
4817
49 48 72 13 72 97 69 79 91 65 72 59 4 29 95 4 88 57 6 41
42
1305
59 53 40 47 90 98 56 36 61 39 69 22 30 23 41 23 67 85 24 37
43
4539
11 54 82 76 1 65 99 10 27 8 30 76 15 21 71 9 49 45 97 36
44
4894
93 98 60 15 42 86 51 23 88 87 28 34 24 25 90 62 81 69 15 74
45
2853
38 36 59 43 74 6 59 37 53 57 46 63 23 48 3 30 89 15 91 53
46
1815
5 9 59 44 54 14 47 76 47 5 75 32 57 33 68 20 43 7 32 49
47
5816
43 78 43 13 41 99 79 83 39 56 78 72 81 92 5 69 24 87 68 77
48
5297
82 80 72 16 15 93 67 58 14 80 34 92 77 2 18 88 70 58 17 13
49
4830
33 88 10 18 38 54 83 99 78 2 4 72 43 12 26 22 74 61 1 37
50
4903
26 52 63 16 24 54 58 29 90 17 23 26 82 32 2 43 44 82 49 34
51
3618
89 30 67 18 91 92 49 35 90 84 69 46 97 38 21 63 23 73 25 31
52
4572
86 62 12 3 49 57 50 49 50 86 33 30 3 67 86 67 89 84 46 15
53
5078
10 8 41 11 23 39 19 89 64 65 11 49 46 93 8 22 96 63 37 32
54
1714
16 45 5 98 63 13 64 79 94 53 5 3 86 80 33 82 80 14 56 45
55
1214
72 77 25 9 88 70 5 82 79 5 54 81 62 75 88 41 44 73 50 50
56
2317
96 90 67 28 1 73 5 92 10 16 42 4 26 59 33 69 69 84 9 81
57
1939
47 52 95 44 30 16 52 45 18 58 12 46 56 51 65 81 7 9 62 46
58
4684
9 39 46 14 85 43 15 42 7 60 40 95 67 7 8 21 10 38 10 93
59
2148
56 95 37 39 22 9 26 21 26 78 30 20 87 65 89 54 15 67 89 13
60
4555
8 86 41 76 94 2 67 51 51 25 51 56 46 6 46 42 55 76 66 47
61
5302
69 15 2 92 39 76 11 30 23 71 94 57 66 59 76 53 27 18 98 50
62
1794
87 98 25 59 70 38 77 70 43 93 24 85 53 30 57 52 55 70 10 70
63
2125
84 59 99 95 85 66 74 2 95 99 28 31 34 67 51 26 2 69 70 21
64
3571
62 22 48 11 7 21 88 20 57 6 84 44 52 41 58 69 82 4 92 41
65
5197
52 43 24 55 65 32 83 82 30 62 69 1 81 32 62 80 42 58 36 12
66
1470
82 85 18 56 43 78 96 13 86 60 44 11 68 63 59 46 88 66 82 18
67
2420
66 93 10 16 4 41 73 92 80 33 98 72 48 7 71 10 84 11 54 28
68
4451
67 6 23 56 60 52 59 91 55 57 36 6 4 8 12 81 38 1 34 22
69
1234
33 46 66 23 90 88 94 2 76 79 21 68 25 89 11 99 69 51 34 60
70
1487
3 51 82 84 73 76 15 80 12 7 9 62 76 51 82 6 31 38 5 69
71
5745
53 97 84 22 21 14 50 38 91 69 48 18 46 81 56 90 5 16 12 49
72
1472
95 79 14 32 25 86 20 54 95 82 30 21 13 9 57 79 3 81 3 38
73
5132
42 46 13 40 33 35 54 45 28 26 15 48 72 13 53 34 37 39 56 80
74
3842
59 71 88 47 48 81 16 19 12 41 21 32 72 27 45 56 14 56 44 52
75
3269
77 18 7 92 25 32 33 65 18 52 43 42 82 74 96 75 35 83 41 45
76
4366
38 33 40 61 27 75 9 35 80 38 91 79 32 59 31 54 61 27 14 34
77
4912
12 13 20 51 37 38 74 66 32 21 49 74 25 98 39 94 43 29 25 3
78
3383
1 3 68 74 63 55 11 26 67 84 86 82 58 31 12 84 38 93 78 61
79
4632
66 32 22 85 28 96 21 18 2 74 36 3 17 98 13 55 48 70 25 96
80
2775
24 28 92 6 88 19 97 32 4 76 41 64 99 48 8 64 89 64 89 99
81
5614
17 48 53 13 27 35 15 51 30 16 10 90 54 74 49 14 86 22 83 49
82
3465
58 8 16 32 94 41 43 23 64 75 75 10 81 76 4 18 37 84 78 78
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1004
71 42 10 8 20 77 2 18 69 75 56 72 73 75 33 6 20 25 23 34
84
1425
88 26 23 43 54 36 1 87 76 36 70 2 93 78 22 27 33 73 51 78
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63 26 88 30 17 24 74 74 92 79 73 49 73 11 30 20 1 81 7 79
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60 95 65 53 74 52 37 10 50 71 57 88 79 71 34 54 8 10 20 64
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1080
86 44 11 24 35 60 61 76 35 82 51 53 54 54 19 30 61 46 30 55
88
4906
8 74 89 2 15 43 3 31 20 70 34 59 72 10 24 58 41 32 30 63
89
2859
8 82 78 11 53 30 75 31 23 22 62 88 37 96 56 35 40 38 30 24
90
5588
44 28 94 33 64 86 41 93 52 39 3 97 68 97 96 66 10 68 63 58
91
5551
99 4 32 27 38 6 86 61 25 8 34 98 22 75 35 85 10 40 82 25
92
5376
80 42 64 35 79 8 51 26 82 22 27 94 94 41 43 78 75 33 40 93
93
5672
76 81 42 40 45 31 65 39 18 79 29 95 37 30 8 15 9 79 39 73
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5671
94 56 74 40 67 80 42 83 2 90 25 93 15 73 5 29 81 64 37 45
95
4086
75 38 87 96 93 82 50 11 29 55 97 95 31 84 65 31 40 36 44 93
96
1806
63 50 63 69 16 2 48 57 70 77 30 6 46 22 64 45 13 62 2 37
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5810
57 12 94 23 59 59 88 81 7 3 28 1 33 8 20 41 10 82 27 64
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1083
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17 30 28 15 52 5 53 55 81 47
1
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22 2 88 57 17 2 43 38 46 44
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79 98 69 23 62 27 48 45 93 76
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37 67 28 9 57 10 83 99 14 4
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53 51 66 2 91 27 93 67 23 49
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59 53 92 43 42 41 95 40 59 5
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64 82 30 73 69 59 48 93 47 25
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67 47 53 96 46 36 93 45 45 67
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60 7 19 17 26 69 31 41 44 23
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62 13 50 55 2 17 10 71 40 87
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83 93 25 59 90 34 57 60 20 50
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73 93 88 18 79 95 21 72 83 18
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55 56 1 31 17 3 56 62 76 23
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40 95 2 46 18 60 6 95 6 96
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13 96 54 77 1 61 86 47 83 37
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62 55 71 59 36 15 2 10 51 29
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56 58 81 98 31 38 89 94 46 19
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28 66 22 23 85 83 28 39 99 26
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53 3 57 18 92 62 62 53 65 56
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71 77 16 17 6 84 63 50 46 33
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5 80 88 70 78 44 52 99 24 53
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73 2 5 73 83 80 12 63 47 6
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95 82 52 38 39 48 13 59 24 95
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4698
49 16 21 77 77 54 99 67 66 84
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17 29 21 74 85 71 11 18 48 13
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81 24 58 79 88 10 70 12 83 6
50
8401
88 89 96 51 25 96 82 9 3 19
51
6004
62 96 37 48 33 23 14 41 74 16
52
3369
35 99 46 16 36 8 39 67 97 80
53
10335
78 15 78 93 32 56 83 52 39 37
54
2868
90 49 87 29 82 35 4 39 80 20
55
5297
36 78 91 28 98 72 86 90 27 62
56
3744
46 48 9 6 3 53 93 25 70 81
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98 64 96 82 46 13 87 13 65 52
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75 3 93 40 68 72 82 81 1 14
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36 63 98 9 11 38 78 3 26 67
60
5131
74 14 31 88 30 1 32 8 46 19
61
9674
86 95 78 51 75 69 82 66 8 86
62
940
67 88 20 48 42 85 24 67 74 1
63
6286
87 9 75 1 93 2 88 51 47 53
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68 61 18 4 36 28 45 54 19 21
65
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1 24 34 77 97 18 48 85 85 33
66
3268
87 38 48 48 1 10 67 10 62 68
67
6533
87 50 49 6 63 70 14 95 33 28
68
1984
7 47 69 1 86 67 34 59 96 25
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2658
34 42 88 32 54 95 76 64 33 69
70
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1 30 30 79 33 72 1 90 5 71
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3280
91 97 34 40 71 64 51 28 23 60
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8989
7 49 22 14 1 19 15 48 43 69
73
4877
6 79 81 20 18 60 67 57 63 99
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7608
46 19 50 86 75 31 57 85 10 53
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4775
3 80 40 40 55 29 3 78 47 77
76
4441
45 30 73 25 62 43 37 18 73 27
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689
55 24 91 94 21 17 15 59 1 29
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8408
92 58 7 73 71 78 50 11 19 83
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2103
67 43 1 44 80 28 75 67 92 22
80
6500
13 6 71 98 5 47 80 36 31 10
81
3906
30 95 72 94 48 78 3 24 29 42
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4713
27 43 8 61 87 77 9 59 68 64
83
9905
19 99 68 65 22 92 28 24 31 80
84
3660
51 22 49 44 5 42 44 39 92 73
85
2405
86 99 7 75 71 86 2 1 48 91
86
7436
20 11 47 4 69 6 71 80 87 38
87
5400
95 99 90 17 75 19 89 58 8 60
88
8689
79 60 59 1 72 28 24 76 90 53
89
5805
48 42 39 12 36 18 73 59 57 38
90
685
83 33 49 78 54 4 28 90 40 19
91
9892
91 68 28 51 24 24 98 92 25 14
92
9000
78 78 22 55 55 57 17 3 49 35
93
2827
41 26 10 53 5 82 27 51 26 10
94
1779
61 77 96 96 40 7 90 1 35 44
95
2539
90 1 2 92 56 4 4 55 90 97
96
5797
57 13 88 82 8 94 13 50 99 17
97
6740
4 67 90 20 19 9 83 15 30 50
98
5913
21 87 69 22 7 57 43 31 5 22
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1778
68 31 44 13 12 82 63 99 52 19
100
9256
87 49 74 40 44 98 68 8 12 70
101
1943
62 90 16 43 66 54 74 44 11 88
102
2314
69 6 90 23 39 2 12 91 72 31
103
5964
79 76 7 30 41 71 69 83 32 7
104
2160
69 94 14 16 60 94 38 75 81 81
105
5000
35 76 47 76 11 69 74 66 21 58
106
753
25 79 48 30 31 51 98 98 81 2
107
8317
68 66 36 59 65 80 86 77 64 89
108
9608
14 51 62 64 16 79 72 8 45 1
109
5659
9 14 1 72 67 85 76 6 4 80
110
3727
74 89 63 61 19 56 53 26 10 52
111
878
61 87 86 13 69 79 94 47 90 15
112
5610
58 1 49 81 56 46 45 55 11 25
113
8024
81 65 48 25 96 71 30 39 88 11
114
7993
52 53 3 90 78 85 39 91 52 97
115
7345
93 19 51 67 36 52 60 78 96 90
116
5943
44 21 80 21 56 42 69 49 92 62
117
5637
57 98 86 70 12 66 12 23 44 69
118
3377
89 90 97 96 37 82 83 92 54 34
119
10135
81 45 4 99 1 91 21 68 28 66
120
2394
69 77 58 64 50 48 25 88 85 54
121
6036
98 54 79 68 43 70 50 9 51 84
122
6761
78 86 28 61 58 21 47 38 21 62
123
7860
70 2 19 36 13 82 43 60 4 71
124
8007
3 3 93 57 55 12 58 2 42 70
125
7718
70 88 88 86 87 94 11 8 43 60
126
7598
62 39 44 10 20 17 63 86 55 54
127
3245
81 56 74 57 84 45 74 62 89 52
128
4953
61 24 18 88 28 68 6 41 4 71
129
8163
65 91 95 59 59 60 23 66 1 9
130
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65 86 2 73 65 93 94 94 97 99
131
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33 80 22 43 56 30 93 54 65 41
132
1742
62 58 7 25 2 5 26 9 38 30
133
1409
19 54 82 37 36 31 49 75 87 23
134
5249
57 57 52 70 41 30 30 43 58 60
135
9063
82 42 17 97 7 71 50 9 47 1
136
7293
78 32 59 29 23 29 47 10 53 67
137
1353
94 5 42 33 25 82 89 79 51 55
138
6480
65 43 51 99 81 20 43 10 40 64
139
8191
14 80 79 34 6 13 32 97 80 21
140
7595
9 86 93 96 67 94 45 39 20 16
141
739
29 47 65 65 5 47 47 30 24 94
142
7977
70 95 27 90 89 57 68 74 77 11
143
8304
90 86 25 52 71 95 13 52 37 90
144
6930
86 40 60 95 86 8 86 90 13 48
145
5996
12 31 72 3 48 46 97 12 29 85
146
2438
40 61 29 64 50 80 2 61 28 34
147
2339
12 12 55 21 54 32 16 34 18 7
148
5848
64 64 58 16 21 7 27 88 22 79
149
4982
32 17 22 70 83 34 38 27 75 95
150
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18 52 58 67 27 33 53 68 24 50
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10491
11 56 61 13 38 33 37 14 79 78
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40 35 89 96 79 18 94 88 99 39
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14 60 67 57 71 29 78 74 35 79
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1948
22 75 14 7 53 19 84 71 45 69
155
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49 10 10 30 2 74 49 14 95 27
156
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95 50 40 96 9 58 25 16 46 42
157
4120
82 66 11 98 49 52 59 46 15 15
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7 53 99 72 79 10 36 47 7 51
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19 58 7 31 39 70 33 54 24 44
160
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95 12 20 11 28 78 15 91 45 71
161
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39 66 78 36 39 59 36 89 20 32
162
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71 81 6 10 70 32 47 59 35 66
163
5464
34 51 71 20 72 20 83 39 61 49
164
6219
89 75 48 26 70 12 24 52 97 8
165
2726
63 71 39 67 38 98 71 91 69 7
166
6507
85 46 58 13 48 18 7 21 78 44
167
6446
60 88 7 60 57 12 6 90 13 1
168
3416
91 58 17 50 11 57 55 58 53 15
169
918
49 73 63 28 38 73 43 74 16 6
170
3139
46 27 73 32 37 91 82 30 94 51
171
9351
10 26 43 49 56 46 40 63 59 91
172
7171
19 38 14 54 64 64 78 19 64 33
173
2127
50 48 66 46 64 92 64 18 72 77
174
4461
65 8 59 15 68 45 96 88 13 69
175
799
41 14 75 49 27 86 27 22 47 28
176
6861
58 58 96 94 36 84 99 43 22 8
177
9690
62 89 28 63 94 15 11 60 9 8
178
3180
45 44 12 96 65 99 91 20 68 48
179
2449
67 16 99 43 89 8 78 32 4 7
180
8742
64 20 63 73 23 87 97 67 67 55
181
4503
6 69 19 19 93 61 23 1 92 51
182
10135
77 67 26 19 14 42 48 42 49 89
183
8757
94 80 8 81 57 25 20 95 23 61
184
1192
24 81 72 82 93 35 99 84 37 82
185
8334
38 82 55 69 60 64 39 37 16 39
186
9610
73 27 67 13 82 74 53 30 39 89
187
8681
59 5 1 85 16 40 3 12 47 47
188
8465
61 44 23 32 69 89 65 87 94 24
189
8425
14 38 35 34 57 4 81 13 71 79
190
3227
59 53 6 57 8 43 47 60 36 86
191
4628
83 16 89 69 52 12 25 92 72 60
192
1319
3 48 93 63 98 28 36 52 67 67
193
9629
46 16 88 49 67 68 44 51 78 10
194
4236
16 31 86 56 19 46 29 91 13 61
195
5509
56 79 37 37 56 23 85 76 68 60
196
9597
40 75 53 54 38 3 26 32 36 68
197
8513
7 14 45 60 75 70 4 81 69 72
198
2882
79 67 32 97 69 81 9 57 28 9
199
7268
55 70 69 44 14 14 59 71 69 47

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Further benchmarks for the bi-objective flow-shop scheduling problem are available at http://www.lifl.fr/~liefooga/benchmarks/

View file

@ -0,0 +1,9 @@
noinst_PROGRAMS = Sch1
Sch1_SOURCES = Sch1.cpp
LDADD = -L$(top_builddir)/src ${EO_DIR}/src/libeo.a ${EO_DIR}/src/utils/libeoutils.a
INCLUDES = -I${EO_DIR}/src/ -I$(top_srcdir)/src