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Initial version of the tutorial.

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Warning: all Makefile's are hand-made, and will only work in Linux
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164
eo/tutorial/Lesson1/FirstBitGA.cpp Normal file
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//-----------------------------------------------------------------------------
// FirstBitGA.cpp
//-----------------------------------------------------------------------------
//*
// An instance of a VERY simple Bitstring Genetic Algorithm
//
//-----------------------------------------------------------------------------
// standard includes
#include <stdexcept> // runtime_error
#include <iostream> // cout
#include <strstream> // ostrstream, istrstream
// the general include for eo
#include <eo>
// REPRESENTATION
//-----------------------------------------------------------------------------
// define your individuals
typedef eoBin<double> Indi; // A bitstring with fitness double
// EVAL
//-----------------------------------------------------------------------------
// a simple fitness function that computes the number of ones of a bitstring
// @param _indi A biststring individual
double binary_value(const Indi & _indi)
{
double sum = 0;
for (unsigned i = 0; i < _indi.size(); i++)
sum += _indi[i];
return sum;
}
// GENERAL
//-----------------------------------------------------------------------------
void main_function(int argc, char **argv)
{
// PARAMETRES
// all parameters are hard-coded!
const unsigned int SEED = 42; // seed for random number generator
const unsigned int T_SIZE = 3; // size for tournament selection
const unsigned int VEC_SIZE = 8; // Number of bits in genotypes
const unsigned int POP_SIZE = 20; // Size of population
const unsigned int MAX_GEN = 100; // Maximum number of generation before STOP
const float CROSS_RATE = 0.8; // Crossover rate
const double P_MUT_PER_BIT = 0.01; // probability of bit-flip mutation
const float MUT_RATE = 1.0; // mutation rate
// GENERAL
//////////////////////////
// Random seed
//////////////////////////
//reproducible random seed: if you don't change SEED above,
// you'll aways get the same result, NOT a random run
rng.reseed(SEED);
// EVAL
/////////////////////////////
// Fitness function
////////////////////////////
// Evaluation: from a plain C++ fn to an EvalFunc Object
eoEvalFuncPtr<Indi> eval( binary_value );
// INIT
////////////////////////////////
// Initilisation of population
////////////////////////////////
// declare the population
eoPop<Indi> pop;
// fill it!
for (unsigned int igeno=0; igeno<POP_SIZE; igeno++)
{
Indi v; // void individual, to be filled
for (unsigned ivar=0; ivar<VEC_SIZE; ivar++)
{
bool r = rng.flip(); // new value, random in {0,1}
v.push_back(r); // append that random value to v
}
eval(v); // evaluate it
pop.push_back(v); // and put it in the population
}
// OUTPUT
// sort pop before printing it!
pop.sort();
// Print (sorted) intial population (raw printout)
cout << "Initial Population" << endl;
cout << pop;
// ENGINE
/////////////////////////////////////
// selection and replacement
////////////////////////////////////
// SELECT
// The robust tournament selection
eoDetTournament<Indi> select(T_SIZE); // T_SIZE in [2,POP_SIZE]
// REPLACE
// The simple GA evolution engine uses generational replacement
// so no replacement procedure is needed
// OPERATORS
//////////////////////////////////////
// The variation operators
//////////////////////////////////////
// CROSSOVER
// 1-point mutation for bitstring
eoBinCrossover<Indi> xover;
// MUTATION
// standard bit-flip mutation for bitstring
eoBinMutation<Indi> mutation(P_MUT_PER_BIT);
// STOP
// CHECKPOINT
//////////////////////////////////////
// termination condition
/////////////////////////////////////
// stop after MAX_GEN generations
eoGenContinue<Indi> continuator(MAX_GEN);
// GENERATION
/////////////////////////////////////////
// the algorithm
////////////////////////////////////////
// standard Generational GA requires as parameters
// selection, evaluation, crossover and mutation, stopping criterion
eoSGA<Indi> gga(select, xover, CROSS_RATE, mutation, MUT_RATE,
eval, continuator);
// Apply algo to pop - that's it!
gga(pop);
// OUTPUT
// Print (sorted) intial population
pop.sort();
cout << "FINAL Population\n" << pop << endl;
// GENERAL
}
// A main that catches the exceptions
int main(int argc, char **argv)
{
#ifdef _MSC_VER
// rng.reseed(42);
int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);
flag |= _CRTDBG_LEAK_CHECK_DF;
_CrtSetDbgFlag(flag);
// _CrtSetBreakAlloc(100);
#endif
try
{
main_function(argc, argv);
}
catch(exception& e)
{
cout << "Exception: " << e.what() << '\n';
}
return 1;
}

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eo/tutorial/Lesson1/FirstRealGA.cpp Normal file
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//-----------------------------------------------------------------------------
// FirstRealGA.cpp
//-----------------------------------------------------------------------------
//*
// An instance of a VERY simple Real-coded Genetic Algorithm
//
//-----------------------------------------------------------------------------
// standard includes
#include <stdexcept> // runtime_error
#include <iostream> // cout
#include <strstream> // ostrstream, istrstream
// the general include for eo
#include <eo>
// REPRESENTATION
//-----------------------------------------------------------------------------
// define your individuals
typedef eoReal<double> Indi;
// EVAL
//-----------------------------------------------------------------------------
// a simple fitness function that computes the euclidian norm of a real vector
// @param _indi A real-valued individual
double real_value(const Indi & _indi)
{
double sum = 0;
for (unsigned i = 0; i < _indi.size(); i++)
sum += _indi[i]*_indi[i];
return (-sum); // maximizing only
}
// GENERAL
//-----------------------------------------------------------------------------
void main_function(int argc, char **argv)
{
// PARAMETRES
// all parameters are hard-coded!
const unsigned int SEED = 42; // seed for random number generator
const unsigned int VEC_SIZE = 8; // Number of object variables in genotypes
const unsigned int POP_SIZE = 20; // Size of population
const unsigned int T_SIZE = 3; // size for tournament selection
const unsigned int MAX_GEN = 500; // Maximum number of generation before STOP
const float CROSS_RATE = 0.8; // Crossover rate
const double EPSILON = 0.01; // range for real uniform mutation
const float MUT_RATE = 0.5; // mutation rate
// GENERAL
//////////////////////////
// Random seed
//////////////////////////
//reproducible random seed: if you don't change SEED above,
// you'll aways get the same result, NOT a random run
rng.reseed(SEED);
// EVAL
/////////////////////////////
// Fitness function
////////////////////////////
// Evaluation: from a plain C++ fn to an EvalFunc Object
eoEvalFuncPtr<Indi> eval( real_value );
// INIT
////////////////////////////////
// Initilisation of population
////////////////////////////////
// declare the population
eoPop<Indi> pop;
// fill it!
for (unsigned int igeno=0; igeno<POP_SIZE; igeno++)
{
Indi v; // void individual, to be filled
for (unsigned ivar=0; ivar<VEC_SIZE; ivar++)
{
double r = 2*rng.uniform() - 1; // new value, random in [-1,1)
v.push_back(r); // append that random value to v
}
eval(v); // evaluate it
pop.push_back(v); // and put it in the population
}
// OUTPUT
// sort pop before printing it!
pop.sort();
// Print (sorted) intial population (raw printout)
cout << "Initial Population" << endl;
cout << pop;
// ENGINE
/////////////////////////////////////
// selection and replacement
////////////////////////////////////
// SELECT
// The robust tournament selection
eoDetTournament<Indi> select(T_SIZE); // T_SIZE in [2,POP_SIZE]
// REPLACE
// eoSGA uses generational replacement by default
// so no replacement procedure has to be given
// OPERATORS
//////////////////////////////////////
// The variation operators
//////////////////////////////////////
// CROSSOVER
// offspring(i) is a linear combination of parent(i)
eoArithmeticCrossover<Indi> xover;
// MUTATION
// offspring(i) uniformly chosen in [parent(i)-epsilon, parent(i)+epsilon]
eoUniformMutation<Indi> mutation(EPSILON);
// STOP
// CHECKPOINT
//////////////////////////////////////
// termination condition
/////////////////////////////////////
// stop after MAX_GEN generations
eoGenContinue<Indi> continuator(MAX_GEN);
// GENERATION
/////////////////////////////////////////
// the algorithm
////////////////////////////////////////
// standard Generational GA requires
// selection, evaluation, crossover and mutation, stopping criterion
eoSGA<Indi> gga(select, xover, CROSS_RATE, mutation, MUT_RATE,
eval, continuator);
// Apply algo to pop - that's it!
gga(pop);
// OUTPUT
// Print (sorted) intial population
pop.sort();
cout << "FINAL Population\n" << pop << endl;
// GENERAL
}
// A main that catches the exceptions
int main(int argc, char **argv)
{
#ifdef _MSC_VER
// rng.reseed(42);
int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);
flag |= _CRTDBG_LEAK_CHECK_DF;
_CrtSetDbgFlag(flag);
// _CrtSetBreakAlloc(100);
#endif
try
{
main_function(argc, argv);
}
catch(exception& e)
{
cout << "Exception: " << e.what() << '\n';
}
return 1;
}

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eo/tutorial/Lesson1/Makefile Normal file
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.cpp: ; g++ -DPACKAGE=\"eo\" -DVERSION=\"0.9.1\" -I. -I../../src -Wall -g -o $@ $*.cpp ../../src/libeo.a ../../src/utils/libeoutils.a
.cpp.o: ; g++ -DPACKAGE=\"eo\" -DVERSION=\"0.9.1\" -I. -I../../src -Wall -g -c $*.cpp
firstGA = FirstRealGA FirstBitGA
ALL = $(firstGA) exercise3
lesson1 : $(firstGA)
clean :
@/bin/rm $(ALL) *.o *~

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eo/tutorial/Lesson1/exercise3.cpp Normal file
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#include <stdexcept> // runtime_error
//-----------------------------------------------------------------------------
// FirstBitGA.cpp
//-----------------------------------------------------------------------------
//*
// An instance of a VERY simple Bitstring Genetic Algorithm
//
//-----------------------------------------------------------------------------
// standard includes
#include <iostream> // cout
#include <strstream> // ostrstream, istrstream
// the general include for eo
#include <eo>
//-----------------------------------------------------------------------------
// define your individuals
typedef eoBin<double> Indi; // A bitstring with fitness double
//-----------------------------------------------------------------------------
/** a simple fitness function that computes the number of ones of a bitstring
@param _indi A biststring individual
*/
double binary_value(const Indi & _indi)
{
double sum = 0;
for (unsigned i = 0; i < _indi.size(); i++)
sum += _indi[i];
return sum;
}
//-----------------------------------------------------------------------------
void main_function(int argc, char **argv)
{
const unsigned int SEED = 42; // seed for random number generator
const unsigned int VEC_SIZE = 8; // Number of bits in genotypes
const unsigned int POP_SIZE = 20; // Size of population
const unsigned int MAX_GEN = 500; // Maximum number of generation before STOP
const float CROSS_RATE = 0.8; // Crossover rate
const double P_MUT_PER_BIT = 0.01; // probability of bit-flip mutation
const float MUT_RATE = 1.0; // mutation rate
//////////////////////////
// Random seed
//////////////////////////
//reproducible random seed: if you don't change SEED above,
// you'll aways get the same result, NOT a random run
rng.reseed(SEED);
/////////////////////////////
// Fitness function
////////////////////////////
// Evaluation: from a plain C++ fn to an EvalFunc Object
eoEvalFuncPtr<Indi> eval( binary_value );
////////////////////////////////
// Initilisation of population
////////////////////////////////
// declare the population
eoPop<Indi> pop;
// fill it!
for (unsigned int igeno=0; igeno<POP_SIZE; igeno++)
{
Indi v; // void individual, to be filled
for (unsigned ivar=0; ivar<VEC_SIZE; ivar++)
{
bool r = rng.flip(); // new value, random in {0,1}
v.push_back(r); // append that random value to v
}
eval(v); // evaluate it
pop.push_back(v); // and put it in the population
}
// sort pop before printing it!
pop.sort();
// Print (sorted) intial population (raw printout)
cout << "Initial Population" << endl;
cout << pop;
/////////////////////////////////////
// selection and replacement
////////////////////////////////////
// solution solution solution: uncomment one of the following,
// comment out the eoDetTournament lines
// The well-known roulette
// eoProportional<Indi> select;
// could also use stochastic binary tournament selection
//
// const double RATE = 0.75;
// eoStochTournament<Indi> select(RATE); // RATE in ]0.5,1]
// The robust tournament selection
const unsigned int T_SIZE = 3; // size for tournament selection
eoDetTournament<Indi> select(T_SIZE); // T_SIZE in [2,POP_SIZE]
// and of course the random selection
// eoSelectRandom<Indi> select;
// The simple GA evolution engine uses generational replacement
// so no replacement procedure is needed
//////////////////////////////////////
// termination condition
/////////////////////////////////////
// stop after MAX_GEN generations
eoGenContinue<Indi> continuator(MAX_GEN);
//////////////////////////////////////
// The variation operators
//////////////////////////////////////
// standard bit-flip mutation for bitstring
eoBinMutation<Indi> mutation(P_MUT_PER_BIT);
// 1-point mutation for bitstring
eoBinCrossover<Indi> xover;
/////////////////////////////////////////
// the algorithm
////////////////////////////////////////
// standard Generational GA requires as parameters
// selection, evaluation, crossover and mutation, stopping criterion
eoSGA<Indi> gga(select, xover, CROSS_RATE, mutation, MUT_RATE,
eval, continuator);
// Apply algo to pop - that's it!
gga(pop);
// Print (sorted) intial population
pop.sort();
cout << "FINAL Population\n" << pop << endl;
}
// A main that catches the exceptions
int main(int argc, char **argv)
{
#ifdef _MSC_VER
// rng.reseed(42);
int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);
flag |= _CRTDBG_LEAK_CHECK_DF;
_CrtSetDbgFlag(flag);
// _CrtSetBreakAlloc(100);
#endif
try
{
main_function(argc, argv);
}
catch(exception& e)
{
cout << "Exception: " << e.what() << '\n';
}
return 1;
}

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eo/tutorial/Lesson2/FirstBitEA.cpp Normal file
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//-----------------------------------------------------------------------------
// FirstBitEA.cpp
//-----------------------------------------------------------------------------
//*
// Still an instance of a VERY simple Bitstring Genetic Algorithm
// (see FirstBitGA.cpp) but now with Breeder - and Combined Ops
//
//-----------------------------------------------------------------------------
// standard includes
#include <stdexcept> // runtime_error
#include <iostream> // cout
#include <strstream> // ostrstream, istrstream
// the general include for eo
#include <eo>
// REPRESENTATION
//-----------------------------------------------------------------------------
// define your individuals
typedef eoBin<double> Indi; // A bitstring with fitness double
// EVALFUNC
//-----------------------------------------------------------------------------
// a simple fitness function that computes the number of ones of a bitstring
// Now in a separate file, and declared as binary_value(const vector<bool> &)
#include "binary_value.h"
// GENERAL
//-----------------------------------------------------------------------------
void main_function(int argc, char **argv)
{
// PARAMETRES
const unsigned int SEED = 42; // seed for random number generator
const unsigned int T_SIZE = 3; // size for tournament selection
const unsigned int VEC_SIZE = 8; // Number of bits in genotypes
const unsigned int POP_SIZE = 20; // Size of population
const unsigned int MAX_GEN = 500; // Maximum number of generation before STOP
const unsigned int MIN_GEN = 10; // Minimum number of generation before ...
const unsigned int STEADY_GEN = 50; // stop after STEADY_GEN gen. without improvelent
const double P_CROSS = 0.8; // Crossover probability
const double P_MUT = 1.0; // mutation probability
const double P_MUT_PER_BIT = 0.01; // internal probability for bit-flip mutation
// some parameters for chosing among different operators
const double onePointRate = 0.5; // rate for 1-pt Xover
const double twoPointsRate = 0.5; // rate for 2-pt Xover
const double URate = 0.5; // rate for Uniform Xover
const double bitFlipRate = 0.5; // rate for bit-flip mutation
const double oneBitRate = 0.5; // rate for one-bit mutation
// GENERAL
//////////////////////////
// Random seed
//////////////////////////
//reproducible random seed: if you don't change SEED above,
// you'll aways get the same result, NOT a random run
rng.reseed(SEED);
// EVAL
/////////////////////////////
// Fitness function
////////////////////////////
// Evaluation: from a plain C++ fn to an EvalFunc Object
// you need to give the full description of the function
eoEvalFuncPtr<Indi, double, const vector<bool>& > eval( binary_value );
// INIT
////////////////////////////////
// Initilisation of population
////////////////////////////////
// based on boolean_generator class (see utils/rnd_generator.h)
eoInitFixedLength<Indi, boolean_generator>
random(VEC_SIZE, boolean_generator());
// Initialization of the population
eoPop<Indi> pop(POP_SIZE, random);
// and evaluate it in one loop
apply<Indi>(eval, pop); // STL syntax
// OUTPUT
// sort pop before printing it!
pop.sort();
// Print (sorted) intial population (raw printout)
cout << "Initial Population" << endl;
cout << pop;
// ENGINE
/////////////////////////////////////
// selection and replacement
////////////////////////////////////
// SELECT
// The robust tournament selection
eoDetTournament<Indi> selectOne(T_SIZE); // T_SIZE in [2,POP_SIZE]
// is now encapsulated in a eoSelectPerc (entage)
eoSelectPerc<Indi> select(selectOne);// by default rate==1
// REPLACE
// And we now have the full slection/replacement - though with
// no replacement (== generational replacement) at the moment :-)
eoNoReplacement<Indi> replace;
// OPERATORS
//////////////////////////////////////
// The variation operators
//////////////////////////////////////
// CROSSOVER
// 1-point crossover for bitstring
eoBinCrossover<Indi> xover1;
// uniform crossover for bitstring
eoBinUxOver<Indi> xoverU;
// 2-pots xover
eoBinNxOver<Indi> xover2(2);
// Combine them with relative rates
eoPropCombinedQuadOp<Indi> xover(xover1, onePointRate);
xover.add(xoverU, URate);
xover.add(xover2, twoPointsRate, true);
// MUTATION
// standard bit-flip mutation for bitstring
eoBinMutation<Indi> mutationBitFlip(P_MUT_PER_BIT);
// mutate exactly 1 bit per individual
eoDetBitFlip<Indi> mutationOneBit;
// Combine them with relative rates
eoPropCombinedMonOp<Indi> mutation(mutationBitFlip, bitFlipRate);
mutation.add(mutationOneBit, oneBitRate, true);
// The operators are encapsulated into an eoTRansform object
eoSGATransform<Indi> transform(xover, P_CROSS, mutation, P_MUT);
// STOP
// CHECKPOINT
//////////////////////////////////////
// termination conditions: use more than one
/////////////////////////////////////
// stop after MAX_GEN generations
eoGenContinue<Indi> genCont(MAX_GEN);
// do MIN_GEN gen., then stop after STEADY_GEN gen. without improvement
eoSteadyFitContinue<Indi> steadyCont(MIN_GEN, STEADY_GEN);
// stop when fitness reaches a target (here VEC_SIZE)
eoFitContinue<Indi> fitCont(VEC_SIZE);
// do stop when one of the above says so
eoCombinedContinue<Indi> continuator(genCont);
continuator.add(steadyCont);
continuator.add(fitCont);
// GENERATION
/////////////////////////////////////////
// the algorithm
////////////////////////////////////////
// Easy EA requires
// selection, transformation, eval, replacement, and stopping criterion
eoEasyEA<Indi> gga(continuator, eval, select, transform, replace);
// Apply algo to pop - that's it!
cout << "\n Here we go\n\n";
gga(pop);
// OUTPUT
// Print (sorted) intial population
pop.sort();
cout << "FINAL Population\n" << pop << endl;
// GENERAL
}
// A main that catches the exceptions
int main(int argc, char **argv)
{
#ifdef _MSC_VER
// rng.reseed(42);
int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);
flag |= _CRTDBG_LEAK_CHECK_DF;
_CrtSetDbgFlag(flag);
// _CrtSetBreakAlloc(100);
#endif
try
{
main_function(argc, argv);
}
catch(exception& e)
{
cout << "Exception: " << e.what() << '\n';
}
return 1;
}

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//-----------------------------------------------------------------------------
// FirstRealEA.cpp
//-----------------------------------------------------------------------------
//*
// Still an instance of a VERY simple Real-coded Genetic Algorithm
// (see FirstBitGA.cpp) but now with Breeder - and Combined Ops
//
//-----------------------------------------------------------------------------
// standard includes
#include <stdexcept> // runtime_error
#include <iostream> // cout
#include <strstream> // ostrstream, istrstream
// the general include for eo
#include <eo>
// REPRESENTATION
//-----------------------------------------------------------------------------
// define your individuals
typedef eoReal<double> Indi;
// EVALFUNC
//-----------------------------------------------------------------------------
// a simple fitness function that computes the euclidian norm of a real vector
// Now in a separate file, and declared as binary_value(const vector<bool> &)
#include "real_value.h"
// GENERAL
//-----------------------------------------------------------------------------
void main_function(int argc, char **argv)
{
// PARAMETRES
const unsigned int SEED = 42; // seed for random number generator
const unsigned int T_SIZE = 3; // size for tournament selection
const unsigned int VEC_SIZE = 8; // Number of object variables in genotypes
const unsigned int POP_SIZE = 20; // Size of population
const unsigned int MAX_GEN = 500; // Maximum number of generation before STOP
const unsigned int MIN_GEN = 10; // Minimum number of generation before ...
const unsigned int STEADY_GEN = 50; // stop after STEADY_GEN gen. without improvelent
const float P_CROSS = 0.8; // Crossover probability
const float P_MUT = 0.5; // mutation probability
const double EPSILON = 0.01; // range for real uniform mutation
// some parameters for chosing among different operators
const double segmentRate = 0.5; // rate for 1-pt Xover
const double arithmeticRate = 0.5; // rate for 2-pt Xover
const double uniformMutRate = 0.5; // rate for bit-flip mutation
const double detMutRate = 0.5; // rate for one-bit mutation
// GENERAL
//////////////////////////
// Random seed
//////////////////////////
//reproducible random seed: if you don't change SEED above,
// you'll aways get the same result, NOT a random run
rng.reseed(SEED);
// EVAL
/////////////////////////////
// Fitness function
////////////////////////////
// Evaluation: from a plain C++ fn to an EvalFunc Object
// you need to give the full description of the function
eoEvalFuncPtr<Indi, double, const vector<double>& > eval( real_value );
// INIT
////////////////////////////////
// Initilisation of population
////////////////////////////////
// based on a uniform generator
eoInitFixedLength<Indi, uniform_generator<double> >
random(VEC_SIZE, uniform_generator<double>(-1.0, 1.0));
// Initialization of the population
eoPop<Indi> pop(POP_SIZE, random);
// and evaluate it in one loop
apply<Indi>(eval, pop); // STL syntax
// OUTPUT
// sort pop before printing it!
pop.sort();
// Print (sorted) intial population (raw printout)
cout << "Initial Population" << endl;
cout << pop;
// ENGINE
/////////////////////////////////////
// selection and replacement
////////////////////////////////////
// SELECT
// The robust tournament selection
eoDetTournament<Indi> selectOne(T_SIZE);
// is now encapsulated in a eoSelectPerc (entage)
eoSelectPerc<Indi> select(selectOne);// by default rate==1
// REPLACE
// And we now have the full slection/replacement - though with
// no replacement (== generational replacement) at the moment :-)
eoNoReplacement<Indi> replace;
// OPERATORS
//////////////////////////////////////
// The variation operators
//////////////////////////////////////
// CROSSOVER
// uniform chooce on segment made by the parents
eoSegmentCrossover<Indi> xoverS;
// uniform choice in hypercube built by the parents
eoArithmeticCrossover<Indi> xoverA;
// Combine them with relative rates
eoPropCombinedQuadOp<Indi> xover(xoverS, segmentRate);
xover.add(xoverA, arithmeticRate, true);
// MUTATION
// offspring(i) uniformly chosen in [parent(i)-epsilon, parent(i)+epsilon]
eoUniformMutation<Indi> mutationU(EPSILON);
// k (=1) coordinates of parents are uniformly modified
eoDetUniformMutation<Indi> mutationD(EPSILON);
// Combine them with relative rates
eoPropCombinedMonOp<Indi> mutation(mutationU, uniformMutRate);
mutation.add(mutationD, detMutRate, true);
// STOP
// CHECKPOINT
//////////////////////////////////////
// termination conditions: use more than one
/////////////////////////////////////
// stop after MAX_GEN generations
eoGenContinue<Indi> genCont(MAX_GEN);
// do MIN_GEN gen., then stop after STEADY_GEN gen. without improvement
eoSteadyFitContinue<Indi> steadyCont(MIN_GEN, STEADY_GEN);
// stop when fitness reaches a target (here VEC_SIZE)
eoFitContinue<Indi> fitCont(0);
// do stop when one of the above says so
eoCombinedContinue<Indi> continuator(genCont);
continuator.add(steadyCont);
continuator.add(fitCont);
// The operators are encapsulated into an eoTRansform object
eoSGATransform<Indi> transform(xover, P_CROSS, mutation, P_MUT);
// GENERATION
/////////////////////////////////////////
// the algorithm
////////////////////////////////////////
// Easy EA requires
// selection, transformation, eval, replacement, and stopping criterion
eoEasyEA<Indi> gga(continuator, eval, select, transform, replace);
// Apply algo to pop - that's it!
cout << "\n Here we go\n\n";
gga(pop);
// OUTPUT
// Print (sorted) intial population
pop.sort();
cout << "FINAL Population\n" << pop << endl;
// GENERAL
}
// A main that catches the exceptions
int main(int argc, char **argv)
{
#ifdef _MSC_VER
// rng.reseed(42);
int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);
flag |= _CRTDBG_LEAK_CHECK_DF;
_CrtSetDbgFlag(flag);
// _CrtSetBreakAlloc(100);
#endif
try
{
main_function(argc, argv);
}
catch(exception& e)
{
cout << "Exception: " << e.what() << '\n';
}
return 1;
}

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.cpp: ; g++ -DPACKAGE=\"eo\" -DVERSION=\"0.9.1\" -I. -I../../src -Wall -g -o $@ $*.cpp ../../src/libeo.a ../../src/utils/libeoutils.a
.cpp.o: ; g++ -DPACKAGE=\"eo\" -DVERSION=\"0.9.1\" -I. -I../../src -Wall -g -c $*.cpp
firstEA = FirstRealEA FirstBitEA
ALL = $(firstEA) exercise1 exercise2 exercise3
lesson2 : $(firstEA)
clean :
@/bin/rm $(ALL) *.o *~

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#include <eo>
//-----------------------------------------------------------------------------
/** Just a simple function that takes binary value of a chromosome and sets
the fitnes.
@param _chrom A binary chromosome
*/
// INIT
double binary_value(const vector<bool>& _chrom)
{
double sum = 0;
for (unsigned i = 0; i < _chrom.size(); i++)
sum += _chrom[i];
return sum;
}

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//-----------------------------------------------------------------------------
// FirstBitEA.cpp
//-----------------------------------------------------------------------------
//*
// Still an instance of a VERY simple Bitstring Genetic Algorithm
// (see FirstBitGA.cpp) but now with Breeder - and Combined Ops
//
//-----------------------------------------------------------------------------
// standard includes
#include <stdexcept> // runtime_error
#include <iostream> // cout
#include <strstream> // ostrstream, istrstream
// the general include for eo
#include <eo>
// REPRESENTATION
//-----------------------------------------------------------------------------
// define your individuals
typedef eoBin<double> Indi; // A bitstring with fitness double
// EVAL
//-----------------------------------------------------------------------------
// a simple fitness function that computes the number of ones of a bitstring
// Now in a separate file, and declared as binary_value(const vector<bool> &)
#include "binary_value.h"
// GENERAL
//-----------------------------------------------------------------------------
void main_function(int argc, char **argv)
{
// PARAMETRES
const unsigned int SEED = 42; // seed for random number generator
const unsigned int T_SIZE = 3; // size for tournament selection
const unsigned int VEC_SIZE = 8; // Number of bits in genotypes
const unsigned int POP_SIZE = 20; // Size of population
const unsigned int MAX_GEN = 500; // Maximum number of generation before STOP
const unsigned int MIN_GEN = 10; // Minimum number of generation before ...
const unsigned int STEADY_GEN = 50; // stop after STEADY_GEN gen. without improvelent
const double P_CROSS = 0.8; // Crossover probability
const double P_MUT = 1.0; // mutation probability
const double P_MUT_PER_BIT = 0.01; // internal probability for bit-flip mutation
// some parameters for chosing among different operators
const double onePointRate = 0.5; // rate for 1-pt Xover
const double twoPointsRate = 0.5; // rate for 2-pt Xover
const double URate = 0.5; // rate for Uniform Xover
const double bitFlipRate = 0.5; // rate for bit-flip mutation
const double oneBitRate = 0.5; // rate for one-bit mutation
// GENERAL
//////////////////////////
// Random seed
//////////////////////////
//reproducible random seed: if you don't change SEED above,
// you'll aways get the same result, NOT a random run
rng.reseed(SEED);
// EVAL
/////////////////////////////
// Fitness function
////////////////////////////
// Evaluation: from a plain C++ fn to an EvalFunc Object
// you need to give the full description of the function
eoEvalFuncPtr<Indi, double, const vector<bool>& > eval( binary_value );
// INIT
////////////////////////////////
// Initilisation of population
////////////////////////////////
// based on boolean_generator class (see utils/rnd_generator.h)
eoInitFixedLength<Indi, boolean_generator>
random(VEC_SIZE, boolean_generator());
// Initialization of the population
eoPop<Indi> pop(POP_SIZE, random);
// and evaluate it in one loop
apply<Indi>(eval, pop); // STL syntax
// OUTPUT
// sort pop before printing it!
pop.sort();
// Print (sorted) intial population (raw printout)
cout << "Initial Population" << endl;
cout << pop;
// ENGINE
/////////////////////////////////////
// selection and replacement
////////////////////////////////////
// SELECT
// The robust tournament selection
eoDetTournament<Indi> selectOne(T_SIZE); // T_SIZE in [2,POP_SIZE]
// solution solution solution solution solution solution solution
// modify the rate in the constructor
eoSelectPerc<Indi> select(selectOne,2.0);// rate is second arg.
// REPLACE
// solution solution solution solution solution solution solution
// eoCommaReplacement keeps the best among offspring
// eoPlusReplacement keeps the best among parents + offspring
// eoCommaReplacement<Indi> replace;
eoPlusReplacement<Indi> replace;
// OPERATORS
//////////////////////////////////////
// The variation operators
//////////////////////////////////////
// CROSSOVER
// 1-point crossover for bitstring
eoBinCrossover<Indi> xover1;
// uniform crossover for bitstring
eoBinUxOver<Indi> xoverU;
// 2-pots xover
eoBinNxOver<Indi> xover2(2);
// Combine them with relative rates
eoPropCombinedQuadOp<Indi> xover(xover1, onePointRate);
xover.add(xoverU, URate);
xover.add(xover2, twoPointsRate, true);
// MUTATION
// standard bit-flip mutation for bitstring
eoBinMutation<Indi> mutationBitFlip(P_MUT_PER_BIT);
// mutate exactly 1 bit per individual
eoDetBitFlip<Indi> mutationOneBit;
// Combine them with relative rates
eoPropCombinedMonOp<Indi> mutation(mutationBitFlip, bitFlipRate);
mutation.add(mutationOneBit, oneBitRate, true);
// The operators are encapsulated into an eoTRansform object
eoSGATransform<Indi> transform(xover, P_CROSS, mutation, P_MUT);
// STOP
// CHECKPOINT
//////////////////////////////////////
// termination conditions: use more than one
/////////////////////////////////////
// stop after MAX_GEN generations
eoGenContinue<Indi> genCont(MAX_GEN);
// do MIN_GEN gen., then stop after STEADY_GEN gen. without improvement
eoSteadyFitContinue<Indi> steadyCont(MIN_GEN, STEADY_GEN);
// stop when fitness reaches a target (here VEC_SIZE)
eoFitContinue<Indi> fitCont(VEC_SIZE);
// do stop when one of the above says so
eoCombinedContinue<Indi> continuator(genCont);
continuator.add(steadyCont);
continuator.add(fitCont);
// GENERATION
/////////////////////////////////////////
// the algorithm
////////////////////////////////////////
// Easy EA requires
// selection, transformation, eval, replacement, and stopping criterion
eoEasyEA<Indi> gga(continuator, eval, select, transform, replace);
// Apply algo to pop - that's it!
gga(pop);
// OUTPUT
// Print (sorted) intial population
pop.sort();
cout << "FINAL Population\n" << pop << endl;
// GENERAL
}
// A main that catches the exceptions
int main(int argc, char **argv)
{
#ifdef _MSC_VER
// rng.reseed(42);
int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);
flag |= _CRTDBG_LEAK_CHECK_DF;
_CrtSetDbgFlag(flag);
// _CrtSetBreakAlloc(100);
#endif
try
{
main_function(argc, argv);
}
catch(exception& e)
{
cout << "Exception: " << e.what() << '\n';
}
return 1;
}

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#include <vector>
//-----------------------------------------------------------------------------
/** Just a simple function that takes an vector<double> and sets the fitnes
to the sphere function. Please use doubles not float!!!
@param _ind A floatingpoint vector
*/
// INIT
double real_value(const std::vector<double>& _ind)
{
double sum = 0;
for (unsigned i = 0; i < _ind.size(); i++)
sum += _ind[i] * _ind[i];
return -sum;
}

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.cpp: ; g++ -DPACKAGE=\"eo\" -DVERSION=\"0.9.1\" -I. -I../../src -Wall -g -o $@ $*.cpp ../../src/libeo.a ../../src/utils/libeoutils.a
.cpp.o: ; g++ -DPACKAGE=\"eo\" -DVERSION=\"0.9.1\" -I. -I../../src -Wall -g -c $*.cpp
secondEA = SecondBitEA
ALL = $(secondEA) exercise1 exercise2 exercise3
lesson3 : $(secondEA)
clean :
@/bin/rm $(ALL) *.o *.sav *.xg *.status *~

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//-----------------------------------------------------------------------------
// SecondGA.cpp
//-----------------------------------------------------------------------------
//*
// Same code than FirstBitEA as far as Evolutionary Computation is concerned
// but now you learn to enter the parameters in a more flexible way
// and to twidle the output to your preferences!
//-----------------------------------------------------------------------------
// standard includes
#include <stdexcept> // runtime_error
#include <iostream> // cout
#include <strstream> // ostrstream, istrstream
#include <fstream>
// the general include for eo
#include <eo>
// EVAL
#include "binary_value.h"
// REPRESENTATION
//-----------------------------------------------------------------------------
// define your genotype and fitness types
typedef eoBin<double> Indi;
// PARAMETRES
//-----------------------------------------------------------------------------
// instead of having all values of useful parameters as constants, read them:
// either on the command line (--option=value or -o=value)
// or in a parameter file (same syntax, order independent,
// # = usual comment character
// or in the environment (TODO)
// note that the parameters are passed by reference so they can be updated
void read_param(int argc, char *argv[],
uint32 & _seed,
unsigned int & _vecSize,
unsigned int & _popSize,
unsigned int & _tSize,
double & _pCross,
double & _pMut,
string & _load_name,
unsigned int & _maxGen,
unsigned int & _minGen,
unsigned int & _steadyGen,
double & _onePointRate,
double & _twoPointsRate,
double & _uRate,
double & _pMutPerBit,
double & _bitFlipRate,
double & _oneBitRate
)
{
// define a parser from the command-line arguments
eoParser parser(argc, argv);
// For each parameter, define Parameters directly in the parser,
// and assign the value to the variable
eoValueParam<uint32>& seedParam = parser.createParam<uint32>(time(0), "seed", "Random number seed", 'S');
_seed = seedParam.value();
eoValueParam<unsigned int>& vecSizeParam = parser.createParam<unsigned int>(8, "vecSize", "Genotype size",'V', "Representation");
_vecSize = vecSizeParam.value();
eoValueParam<unsigned int>& popSizeParam = parser.createParam<unsigned int>(10, "popSize", "Population size",'P', "Evolution");
_popSize = popSizeParam.value();
eoValueParam<unsigned int>& tSizeParam = parser.createParam<unsigned int>(10, "tSize", "Tournament size",'T', "Evolution");
_tSize = tSizeParam.value();
eoValueParam<string>& load_nameParam = parser.createParam<string>("", "Load","A save file to restart from",'L', "Persistence");
_load_name = load_nameParam.value();
eoValueParam<unsigned int>& maxGenParam = parser.createParam<unsigned int>(100, "maxGen", "Maximum number of generations",'G', "Stopping criterion");
_maxGen = maxGenParam.value();
eoValueParam<unsigned int>& minGenParam = parser.createParam<unsigned int>(100, "minGen", "Minimum number of generations",'g', "Stopping criterion");
_minGen = minGenParam.value();
eoValueParam<unsigned int>& steadyGenParam = parser.createParam<unsigned int>(100, "steadyGen", "Number of generations with no improvement",'s', "Stopping criterion");
_steadyGen = steadyGenParam.value();
eoValueParam<double>& pCrossParam = parser.createParam<double>(0.6, "pCross", "Probability of Crossover", 'C', "Genetic Operators");
_pCross = pCrossParam.value();
eoValueParam<double>& pMutParam = parser.createParam<double>(0.1, "pMut", "Probability of Mutation", 'M', "Genetic Operators");
_pMut = pMutParam.value();
eoValueParam<double>& onePointRateParam = parser.createParam<double>(1, "onePointRate", "Relative rate for one point crossover", '1', "Genetic Operators");
_onePointRate = onePointRateParam.value();
eoValueParam<double>& twoPointsRateParam = parser.createParam<double>(1, "twoPointRate", "Relative rate for two point crossover", '2', "Genetic Operators");
_twoPointsRate = twoPointsRateParam.value();
eoValueParam<double>& uRateParam = parser.createParam<double>(2, "uRate", "Relative rate for uniform crossover", 'U', "Genetic Operators");
_uRate = uRateParam.value();
eoValueParam<double>& pMutPerBitParam = parser.createParam<double>(0.01, "pMutPerBit", "Probability of flipping 1 bit in bit-flip mutation", 'b', "Genetic Operators");
_pMutPerBit = pMutPerBitParam.value();
eoValueParam<double>& bitFlipRateParam = parser.createParam<double>(0.01, "bitFlipRate", "Relative rate for bit-flip mutation", 'B', "Genetic Operators");
_bitFlipRate = bitFlipRateParam.value();
eoValueParam<double>& oneBitRateParam = parser.createParam<double>(0.01, "oneBitRate", "Relative rate for deterministic bit-flip mutation", 'D', "Genetic Operators");
_oneBitRate = oneBitRateParam.value();
// the name of the "status" file where all actual parameter values will be saved
string str_status = parser.ProgramName() + ".status";
eoValueParam<string>& status_nameParam = parser.createParam<string>(str_status.c_str(), "status","Status file",'S', "Persistence");
// do the following AFTER ALL PARAMETERS HAVE BEEN PROCESSED
// i.e. in case you need parameters somewhere else, postpone these
if (parser.userNeedsHelp())
{
parser.printHelp(cout);
exit(1);
}
if (status_nameParam.value() != "")
{
ofstream os(status_nameParam.value().c_str());
os << parser; // and you can use that file as parameter file
}
}
// GENERAL
// now the main_function: nothing changed, except input/output
void main_function(int argc, char **argv)
{
// PARAMETRES
uint32 seed;
// decription of genotype
unsigned int vecSize;
// parameters for evolution engine
unsigned int popSize;
unsigned int tSize;
// operators probabilities at the algorithm level
double pCross;
double pMut;
// init and stop
string load_name;
unsigned int maxGen;
unsigned int minGen;
unsigned int steadyGen;
// rates for crossovers
double onePointRate;
double twoPointsRate;
double URate;
// rates and private parameters for mutations;
double pMutPerBit;
double bitFlipRate;
double oneBitRate;
// Now read the parameters of the program
read_param(argc, argv, seed, vecSize, popSize, tSize,
pCross, pMut, load_name, maxGen, minGen, steadyGen,
onePointRate, twoPointsRate, URate,
pMutPerBit, bitFlipRate, oneBitRate );
// EVAL
/////////////////////////////
// Fitness function
////////////////////////////
// Evaluation: from a plain C++ fn to an EvalFunc Object ...
eoEvalFuncPtr<Indi, double, const vector<bool>& > plainEval( binary_value );
// ... to an object that counts the nb of actual evaluations
eoEvalFuncCounter<Indi> eval(plainEval);
// INIT
////////////////////////////////
// Initilisation of population
////////////////////////////////
// Either load or initialize
// create an empty pop
eoPop<Indi> pop;
// create a state for reading
eoState inState; // a state for loading - WITHOUT the parser
// register the rng and the pop in the state, so they can be loaded,
// and the present run will be the exact conitnuation of the saved run
// eventually with different parameters
inState.registerObject(rng);
inState.registerObject(pop);
if (load_name != "")
{
inState.load(load_name); // load the pop and the rng
// the fitness is read in the file:
// do only evaluate the pop if the fitness has changed
}
else
{
rng.reseed(seed);
// a Indi random initializer
// based on boolean_generator class (see utils/rnd_generator.h)
eoInitFixedLength<Indi, boolean_generator>
random(vecSize, boolean_generator());
// Init pop from the randomizer: need to use the append function
pop.append(popSize, random);
// and evaluate pop (STL syntax)
apply<Indi>(eval, pop);
} // end of initializatio of the population
// OUTPUT
// sort pop for pretty printout
pop.sort();
// Print (sorted) intial population (raw printout)
cout << "Initial Population" << endl << pop << endl;
// ENGINE
/////////////////////////////////////
// selection and replacement
////////////////////////////////////
// SELECT
// The robust tournament selection
eoDetTournament<Indi> selectOne(tSize); // tSize in [2,POPSIZE]
// is now encapsulated in a eoSelectPerc (entage)
eoSelectPerc<Indi> select(selectOne);// by default rate==1
// REPLACE
// And we now have the full slection/replacement - though with
// no replacement (== generational replacement) at the moment :-)
eoNoReplacement<Indi> replace;
// OPERATORS
//////////////////////////////////////
// The variation operators
//////////////////////////////////////
// CROSSOVER
// 1-point crossover for bitstring
eoBinCrossover<Indi> xover1;
// uniform crossover for bitstring
eoBinUxOver<Indi> xoverU;
// 2-pots xover
eoBinNxOver<Indi> xover2(2);
// Combine them with relative rates
eoPropCombinedQuadOp<Indi> xover(xover1, onePointRate);
xover.add(xoverU, URate);
xover.add(xover2, twoPointsRate, true);
// MUTATION
// standard bit-flip mutation for bitstring
eoBinMutation<Indi> mutationBitFlip(pMutPerBit);
// mutate exactly 1 bit per individual
eoDetBitFlip<Indi> mutationOneBit;
// Combine them with relative rates
eoPropCombinedMonOp<Indi> mutation(mutationBitFlip, bitFlipRate);
mutation.add(mutationOneBit, oneBitRate, true);
// The operators are encapsulated into an eoTRansform object
eoSGATransform<Indi> transform(xover, pCross, mutation, pMut);
// STOP
//////////////////////////////////////
// termination condition see FirstBitEA.cpp
/////////////////////////////////////
eoGenContinue<Indi> genCont(maxGen);
eoSteadyFitContinue<Indi> steadyCont(minGen, steadyGen);
eoFitContinue<Indi> fitCont(vecSize);
eoCombinedContinue<Indi> continuator(genCont);
continuator.add(steadyCont);
continuator.add(fitCont);
// CHECKPOINT
// but now you want to make many different things every generation
// (e.g. statistics, plots, ...).
// the class eoCheckPoint is dedicated to just that:
// Declare a checkpoint (from a continuator: an eoCheckPoint
// IS AN eoContinue and will be called in the loop of all algorithms)
eoCheckPoint<Indi> checkpoint(continuator);
// Create a counter parameter
eoValueParam<unsigned> generationCounter(0, "Gen.");
// Create an incrementor (sub-class of eoUpdater). Note that the
// parameter's value is passed by reference,
// so every time the incrementer is updated (every generation),
// the data in generationCounter will change.
eoIncrementor<unsigned> increment(generationCounter.value());
// Add it to the checkpoint,
// so the counter is updated (here, incremented) every generation
checkpoint.add(increment);
// now some statistics on the population:
// Best fitness in population
eoBestFitnessStat<Indi> bestStat;
// Second moment stats: average and stdev
eoSecondMomentStats<Indi> SecondStat;
// Add them to the checkpoint to get them called at the appropriate time
checkpoint.add(bestStat);
checkpoint.add(SecondStat);
// The Stdout monitor will print parameters to the screen ...
eoStdoutMonitor monitor(false);
// when called by the checkpoint (i.e. at every generation)
checkpoint.add(monitor);
// the monitor will output a series of parameters: add them
monitor.add(generationCounter);
monitor.add(eval); // because now eval is an eoEvalFuncCounter!
monitor.add(bestStat);
monitor.add(SecondStat);
// A file monitor: will print parameters to ... a File, yes, you got it!
eoFileMonitor fileMonitor("stats.xg", " ");
// the checkpoint mechanism can handle multiple monitors
checkpoint.add(fileMonitor);
// the fileMonitor can monitor parameters, too, but you must tell it!
fileMonitor.add(generationCounter);
fileMonitor.add(bestStat);
fileMonitor.add(SecondStat);
// Last type of item the eoCheckpoint can handle: state savers:
eoState outState;
// Register the algorithm into the state (so it has something to save!!)
outState.registerObject(rng);
outState.registerObject(pop);
// and feed the state to state savers
// save state every 100th generation
eoCountedStateSaver stateSaver1(100, outState, "generation");
// save state every 1 seconds
eoTimedStateSaver stateSaver2(1, outState, "time");
// Don't forget to add the two savers to the checkpoint
checkpoint.add(stateSaver1);
checkpoint.add(stateSaver2);
// and that's it for the (control and) output
// GENERATION
/////////////////////////////////////////
// the algorithm
////////////////////////////////////////
// Easy EA requires
// selection, transformation, eval, replacement, and stopping criterion
eoEasyEA<Indi> gga(checkpoint, eval, select, transform, replace);
// Apply algo to pop - that's it!
gga(pop);
// OUTPUT
// Print (sorted) intial population
pop.sort();
cout << "FINAL Population\n" << pop << endl;
// GENERAL
}
// A main that catches the exceptions
int main(int argc, char **argv)
{
#ifdef _MSC_VER
int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);
flag |= _CRTDBG_LEAK_CHECK_DF;
_CrtSetDbgFlag(flag);
// _CrtSetBreakAlloc(100);
#endif
try
{
main_function(argc, argv);
}
catch(exception& e)
{
cout << "Exception: " << e.what() << '\n';
}
return 1;
}

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#include <eo>
//-----------------------------------------------------------------------------
/** Just a simple function that takes binary value of a chromosome and sets
the fitnes.
@param _chrom A binary chromosome
*/
// INIT
double binary_value(const vector<bool>& _chrom)
{
double sum = 0;
for (unsigned i = 0; i < _chrom.size(); i++)
sum += _chrom[i];
return sum;
}

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//-----------------------------------------------------------------------------
// SecondBitGA.cpp
//-----------------------------------------------------------------------------
//*
// Same code than FirstBitEA as far as Evolutionary Computation is concerned
// but now you learn to enter the parameters in a more flexible way
// and to twidle the output to your preferences!
//-----------------------------------------------------------------------------
// standard includes
#include <stdexcept> // runtime_error
#include <iostream> // cout
#include <strstream> // ostrstream, istrstream
#include <fstream>
// the general include for eo
#include <eo>
#include <utils/eoGnuplot1DMonitor.h>
// EVAL
#include "binary_value.h"
// REPRESENTATION
//-----------------------------------------------------------------------------
// define your genotype and fitness types
typedef eoBin<double> Indi;
// PARAMETRES
//-----------------------------------------------------------------------------
// instead of having all values of useful parameters as constants, read them:
// either on the command line (--option=value or -o=value)
// or in a parameter file (same syntax, order independent,
// # = usual comment character
// or in the environment (TODO)
// note that the parameters are passed by reference so they can be updated
void read_param(int argc, char *argv[],
uint32 & _seed,
unsigned int & _vecSize,
unsigned int & _popSize,
unsigned int & _tSize,
double & _pCross,
double & _pMut,
string & _load_name,
unsigned int & _maxGen,
unsigned int & _minGen,
unsigned int & _steadyGen,
double & _onePointRate,
double & _twoPointsRate,
double & _uRate,
double & _pMutPerBit,
double & _bitFlipRate,
double & _oneBitRate
)
{
// define a parser from the command-line arguments
eoParser parser(argc, argv);
// For each parameter, define Parameters directly in the parser,
// and assign the value to the variable
eoValueParam<uint32>& seedParam = parser.createParam<uint32>(time(0), "seed", "Random number seed", 'S');
_seed = seedParam.value();
eoValueParam<unsigned int>& vecSizeParam = parser.createParam<unsigned int>(8, "vecSize", "Genotype size",'V', "Representation");
_vecSize = vecSizeParam.value();
eoValueParam<unsigned int>& popSizeParam = parser.createParam<unsigned int>(10, "popSize", "Population size",'P', "Evolution");
_popSize = popSizeParam.value();
eoValueParam<unsigned int>& tSizeParam = parser.createParam<unsigned int>(10, "tSize", "Tournament size",'T', "Evolution");
_tSize = tSizeParam.value();
eoValueParam<string>& load_nameParam = parser.createParam<string>("", "Load","A save file to restart from",'L', "Persistence");
_load_name = load_nameParam.value();
eoValueParam<unsigned int>& maxGenParam = parser.createParam<unsigned int>(100, "maxGen", "Maximum number of generations",'G', "Stopping criterion");
_maxGen = maxGenParam.value();
eoValueParam<unsigned int>& minGenParam = parser.createParam<unsigned int>(100, "minGen", "Minimum number of generations",'g', "Stopping criterion");
_minGen = minGenParam.value();
eoValueParam<unsigned int>& steadyGenParam = parser.createParam<unsigned int>(100, "steadyGen", "Number of generations with no improvement",'s', "Stopping criterion");
_steadyGen = steadyGenParam.value();
eoValueParam<double>& pCrossParam = parser.createParam<double>(0.6, "pCross", "Probability of Crossover", 'C', "Genetic Operators");
_pCross = pCrossParam.value();
eoValueParam<double>& pMutParam = parser.createParam<double>(0.1, "pMut", "Probability of Mutation", 'M', "Genetic Operators");
_pMut = pMutParam.value();
eoValueParam<double>& onePointRateParam = parser.createParam<double>(1, "onePointRate", "Relative rate for one point crossover", '1', "Genetic Operators");
_onePointRate = onePointRateParam.value();
eoValueParam<double>& twoPointsRateParam = parser.createParam<double>(1, "twoPointRate", "Relative rate for two point crossover", '2', "Genetic Operators");
_twoPointsRate = twoPointsRateParam.value();
eoValueParam<double>& uRateParam = parser.createParam<double>(2, "uRate", "Relative rate for uniform crossover", 'U', "Genetic Operators");
_uRate = uRateParam.value();
eoValueParam<double>& pMutPerBitParam = parser.createParam<double>(0.01, "pMutPerBit", "Probability of flipping 1 bit in bit-flip mutation", 'b', "Genetic Operators");
_pMutPerBit = pMutPerBitParam.value();
eoValueParam<double>& bitFlipRateParam = parser.createParam<double>(0.01, "bitFlipRate", "Relative rate for bit-flip mutation", 'B', "Genetic Operators");
_bitFlipRate = bitFlipRateParam.value();
eoValueParam<double>& oneBitRateParam = parser.createParam<double>(0.01, "oneBitRate", "Relative rate for deterministic bit-flip mutation", 'D', "Genetic Operators");
_oneBitRate = oneBitRateParam.value();
// the name of the "status" file where all actual parameter values will be saved
string str_status = parser.ProgramName() + ".status";
eoValueParam<string>& status_nameParam = parser.createParam<string>(str_status.c_str(), "status","Status file",'S', "Persistence");
// do the following AFTER ALL PARAMETERS HAVE BEEN PROCESSED
// i.e. in case you need parameters somewhere else, postpone these
if (parser.userNeedsHelp())
{
parser.printHelp(cout);
exit(1);
}
if (status_nameParam.value() != "")
{
ofstream os(status_nameParam.value().c_str());
os << parser; // and you can use that file as parameter file
}
}
// GENERAL
// now the main_function: nothing changed, except input/output
void main_function(int argc, char **argv)
{
// PARAMETRES
uint32 seed;
// decription of genotype
unsigned int vecSize;
// parameters for evolution engine
unsigned int popSize;
unsigned int tSize;
// operators probabilities at the algorithm level
double pCross;
double pMut;
// init and stop
string load_name;
unsigned int maxGen;
unsigned int minGen;
unsigned int steadyGen;
// rates for crossovers
double onePointRate;
double twoPointsRate;
double URate;
// rates and private parameters for mutations;
double pMutPerBit;
double bitFlipRate;
double oneBitRate;
// Now read the parameters of the program
read_param(argc, argv, seed, vecSize, popSize, tSize,
pCross, pMut, load_name, maxGen, minGen, steadyGen,
onePointRate, twoPointsRate, URate,
pMutPerBit, bitFlipRate, oneBitRate );
// EVAL
/////////////////////////////
// Fitness function
////////////////////////////
// Evaluation: from a plain C++ fn to an EvalFunc Object ...
eoEvalFuncPtr<Indi, double, const vector<bool>& > plainEval( binary_value );
// ... to an object that counts the nb of actual evaluations
eoEvalFuncCounter<Indi> eval(plainEval);
// INIT
////////////////////////////////
// Initilisation of population
////////////////////////////////
// Either load or initialize
// create an empty pop
eoPop<Indi> pop;
// create a state for reading
eoState inState; // a state for loading - WITHOUT the parser
// register the rng and the pop in the state, so they can be loaded,
// and the present run will be the exact conitnuation of the saved run
// eventually with different parameters
inState.registerObject(rng);
inState.registerObject(pop);
if (load_name != "")
{
inState.load(load_name); // load the pop and the rng
// the fitness is read in the file:
// do only evaluate the pop if the fitness has changed
}
else
{
rng.reseed(seed);
// a Indi random initializer
// based on boolean_generator class (see utils/rnd_generator.h)
eoInitFixedLength<Indi, boolean_generator>
random(vecSize, boolean_generator());
// Init pop from the randomizer: need to use the append function
pop.append(popSize, random);
// and evaluate pop (STL syntax)
apply<Indi>(eval, pop);
} // end of initializatio of the population
// OUTPUT
// sort pop for pretty printout
pop.sort();
// Print (sorted) intial population (raw printout)
cout << "Initial Population" << endl << pop << endl;
// ENGINE
/////////////////////////////////////
// selection and replacement
////////////////////////////////////
// SELECT
// The robust tournament selection
eoDetTournament<Indi> selectOne(tSize); // tSize in [2,POPSIZE]
// is now encapsulated in a eoSelectPerc (entage)
eoSelectPerc<Indi> select(selectOne);// by default rate==1
// REPLACE
// And we now have the full slection/replacement - though with
// no replacement (== generational replacement) at the moment :-)
eoNoReplacement<Indi> replace;
// OPERATORS
//////////////////////////////////////
// The variation operators
//////////////////////////////////////
// CROSSOVER
// 1-point crossover for bitstring
eoBinCrossover<Indi> xover1;
// uniform crossover for bitstring
eoBinUxOver<Indi> xoverU;
// 2-pots xover
eoBinNxOver<Indi> xover2(2);
// Combine them with relative rates
eoPropCombinedQuadOp<Indi> xover(xover1, onePointRate);
xover.add(xoverU, URate);
xover.add(xover2, twoPointsRate, true);
// MUTATION
// standard bit-flip mutation for bitstring
eoBinMutation<Indi> mutationBitFlip(pMutPerBit);
// mutate exactly 1 bit per individual
eoDetBitFlip<Indi> mutationOneBit;
// Combine them with relative rates
eoPropCombinedMonOp<Indi> mutation(mutationBitFlip, bitFlipRate);
mutation.add(mutationOneBit, oneBitRate, true);
// The operators are encapsulated into an eoTRansform object
eoSGATransform<Indi> transform(xover, pCross, mutation, pMut);
// STOP
//////////////////////////////////////
// termination condition see FirstBitEA.cpp
/////////////////////////////////////
eoGenContinue<Indi> genCont(maxGen);
eoSteadyFitContinue<Indi> steadyCont(minGen, steadyGen);
eoFitContinue<Indi> fitCont(vecSize);
eoCombinedContinue<Indi> continuator(genCont);
continuator.add(steadyCont);
continuator.add(fitCont);
// CHECKPOINT
// but now you want to make many different things every generation
// (e.g. statistics, plots, ...).
// the class eoCheckPoint is dedicated to just that:
// Declare a checkpoint (from a continuator: an eoCheckPoint
// IS AN eoContinue and will be called in the loop of all algorithms)
eoCheckPoint<Indi> checkpoint(continuator);
// Create a counter parameter
eoValueParam<unsigned> generationCounter(0, "Gen.");
// Create an incrementor (sub-class of eoUpdater). Note that the
// parameter's value is passed by reference,
// so every time the incrementer is updated (every generation),
// the data in generationCounter will change.
eoIncrementor<unsigned> increment(generationCounter.value());
// Add it to the checkpoint,
// so the counter is updated (here, incremented) every generation
checkpoint.add(increment);
// now some statistics on the population:
// Best fitness in population
eoBestFitnessStat<Indi> bestStat;
eoAverageStat<Indi> averageStat;
// Second moment stats: average and stdev
eoSecondMomentStats<Indi> SecondStat;
// Add them to the checkpoint to get them called at the appropriate time
checkpoint.add(bestStat);
checkpoint.add(averageStat);
checkpoint.add(SecondStat);
// The Stdout monitor will print parameters to the screen ...
eoStdoutMonitor monitor(false);
// when called by the checkpoint (i.e. at every generation)
checkpoint.add(monitor);
// the monitor will output a series of parameters: add them
monitor.add(generationCounter);
monitor.add(eval); // because now eval is an eoEvalFuncCounter!
monitor.add(bestStat);
monitor.add(SecondStat);
// A file monitor: will print parameters to ... a File, yes, you got it!
eoFileMonitor fileMonitor("stats.xg", " ");
eoGnuplot1DMonitor gnuMonitor("best_average.xg");
// the checkpoint mechanism can handle multiple monitors
checkpoint.add(fileMonitor);
checkpoint.add(gnuMonitor);
// the fileMonitor can monitor parameters, too, but you must tell it!
fileMonitor.add(generationCounter);
fileMonitor.add(bestStat);
fileMonitor.add(SecondStat);
// the fileMonitor can monitor parameters, too, but you must tell it!
gnuMonitor.add(eval);
gnuMonitor.add(bestStat);
gnuMonitor.add(averageStat);
// Last type of item the eoCheckpoint can handle: state savers:
eoState outState;
// Register the algorithm into the state (so it has something to save!!)
outState.registerObject(rng);
outState.registerObject(pop);
// and feed the state to state savers
// save state every 100th generation
eoCountedStateSaver stateSaver1(100, outState, "generation");
// save state every 1 seconds
eoTimedStateSaver stateSaver2(1, outState, "time");
// Don't forget to add the two savers to the checkpoint
checkpoint.add(stateSaver1);
checkpoint.add(stateSaver2);
// and that's it for the (control and) output
// GENERATION
/////////////////////////////////////////
// the algorithm
////////////////////////////////////////
// Easy EA requires
// selection, transformation, eval, replacement, and stopping criterion
eoEasyEA<Indi> gga(checkpoint, eval, select, transform, replace);
// Apply algo to pop - that's it!
gga(pop);
// OUTPUT
// Print (sorted) intial population
pop.sort();
cout << "FINAL Population\n" << pop << endl;
// GENERAL
}
// A main that catches the exceptions
int main(int argc, char **argv)
{
#ifdef _MSC_VER
int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);
flag |= _CRTDBG_LEAK_CHECK_DF;
_CrtSetDbgFlag(flag);
// _CrtSetBreakAlloc(100);
#endif
try
{
main_function(argc, argv);
}
catch(exception& e)
{
cout << "Exception: " << e.what() << '\n';
}
return 1;
}

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<font color="#FF0000">FirstBitEA.cpp</font></h1></center>
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//-----------------------------------------------------------------------------<br>
// FirstBitEA.cpp<br>
//-----------------------------------------------------------------------------<br>
//*<br>
// Still an instance of a VERY simple Bitstring Genetic Algorithm <br>
// (see FirstBitGA.cpp) but now with &nbsp;Breeder - and Combined Ops<br>
//<br>
//-----------------------------------------------------------------------------<br>
// standard includes<br>
<b>#include &lt;stdexcept> &nbsp;</b>// runtime_error <br>
<b>#include &lt;iostream> &nbsp; &nbsp;</b>// cout<br>
<b>#include &lt;strstream> &nbsp;</b>// ostrstream, istrstream<br>
// the general include for eo<br>
<b>#include &lt;eo></b><br>
</font></tt>
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//-----------------------------------------------------------------------------<br>
// define your individuals<br>
<b>typedef eoBin&lt;double> Indi; </b>// A bitstring with fitness double<br>
</font></tt>
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<a NAME="evalfunc"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCCC" NOSAVE >
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//-----------------------------------------------------------------------------<br>
// a simple fitness function that computes the number of ones of a bitstring<br>
// Now in a separate file, and declared as binary_value(const vector&lt;bool> &)<br>
<b>#include "binary_value.h"</b><br>
</font></tt>
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//-----------------------------------------------------------------------------<br>
<b>void main_function(int argc, char **argv)</b><br>
<b>{</b><br>
</font></tt>
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<a NAME="parametres"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#CCFFFF" NOSAVE >
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<b> &nbsp;const unsigned int SEED = 42; </b>// seed for random number generator<br>
<b> &nbsp;const unsigned int T_SIZE = 3; </b>// size for tournament selection<br>
<b> &nbsp;const unsigned int VEC_SIZE = 8; </b>// Number of bits in genotypes<br>
<b> &nbsp;const unsigned int POP_SIZE = 20; </b>// Size of population<br>
<b> &nbsp;const unsigned int MAX_GEN = 500; </b>// Maximum number of generation before STOP<br>
<b> &nbsp;const float CROSS_RATE = 0.8; </b>// Crossover rate<br>
<b> &nbsp;const double P_MUT_PER_BIT = 0.01; </b>// probability of bit-flip mutation<br>
<b> &nbsp;const float MUT_RATE = 1.0; </b>// mutation rate<br>
<b> &nbsp;</b>// some parameters for chosing among different operators<br>
<b> &nbsp;const double onePointRate = 0.5; &nbsp; &nbsp; &nbsp; &nbsp;</b>// rate for 1-pt Xover<br>
<b> &nbsp;const double twoPointsRate = 0.5; &nbsp; &nbsp; &nbsp; &nbsp;</b>// rate for 2-pt Xover<br>
<b> &nbsp;const double URate = 0.5; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// rate for Uniform Xover<br>
<b> &nbsp;const double bitFlipRate = 0.5; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// rate for bit-flip mutation<br>
<b> &nbsp;const double oneBitRate = 0.5; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// rate for one-bit mutation<br>
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<b> &nbsp;</b>//////////////////////////<br>
<b> &nbsp;</b>// &nbsp;Random seed<br>
<b> &nbsp;</b>//////////////////////////<br>
<b> &nbsp;</b>//reproducible random seed: if you don't change SEED above, <br>
<b> &nbsp;</b>// you'll aways get the same result, NOT a random run<br>
<b> &nbsp;rng.reseed(SEED);</b><br>
</font></tt>
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<b> &nbsp;</b>/////////////////////////////<br>
<b> &nbsp;</b>// Fitness function<br>
<b> &nbsp;</b>////////////////////////////<br>
<b> &nbsp;</b>// Evaluation: from a plain C++ fn to an EvalFunc Object<br>
<b> &nbsp;</b>// you need to give the full description of the function<br>
<b> &nbsp;eoEvalFuncPtr&lt;Indi, double, const vector&lt;bool>& > eval( &nbsp;binary_value );</b><br>
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<a NAME="init"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCFF" NOSAVE >
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<b> &nbsp;</b>////////////////////////////////<br>
<b> &nbsp;</b>// Initilisation of population<br>
<b> &nbsp;</b>////////////////////////////////<br>
<b> &nbsp;</b>// based on boolean_generator class (see utils/rnd_generator.h)<br>
<b> &nbsp;eoInitFixedLength&lt;Indi, boolean_generator> </b><br>
<b> &nbsp; &nbsp; &nbsp;random(VEC_SIZE, boolean_generator());</b><br>
<b> &nbsp;</b>// Initialization of the population<br>
<b> &nbsp;eoPop&lt;Indi> pop(POP_SIZE, random);</b><br>
<b> &nbsp;</b>// and evaluate it in one loop<br>
<b> &nbsp;apply&lt;Indi>(eval, pop); </b>// STL syntax<br>
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<b> &nbsp;</b>// sort pop before printing it!<br>
<b> &nbsp;pop.sort();</b><br>
<b> &nbsp;</b>// Print (sorted) intial population (raw printout)<br>
<b> &nbsp;cout &lt;&lt; "Initial Population" &lt;&lt; endl;</b><br>
<b> &nbsp;cout &lt;&lt; pop;</b><br>
</font></tt>
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<a NAME="engine"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#99FFCC" NOSAVE >
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<b> &nbsp;</b>/////////////////////////////////////<br>
<b> &nbsp;</b>// selection and replacement<br>
<b> &nbsp;</b>////////////////////////////////////<br>
</font></tt>
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<a NAME="select"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#99FFCC" NOSAVE >
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<b> &nbsp;</b>// The robust tournament selection<br>
<b> &nbsp;eoDetTournament&lt;Indi> selectOne(T_SIZE); &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// T_SIZE in [2,POP_SIZE]<br>
<a NAME="select_encapsulate"></a>
<b> &nbsp;</b>// is now encapsulated in a eoSelectPerc (entage)<br>
<b> &nbsp;eoSelectPerc&lt;Indi> select(selectOne);</b>// by default rate==1<br>
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<b> &nbsp;</b>// And we now have the full slection/replacement - though with <br>
<b> &nbsp;</b>// no replacement (== generational replacement) at the moment :-)<br>
<b> &nbsp;eoNoReplacement&lt;Indi> replace; </b><br>
</font></tt>
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<a NAME="operators"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCFF" NOSAVE >
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<b> &nbsp;</b>//////////////////////////////////////<br>
<b> &nbsp;</b>// The variation operators<br>
<b> &nbsp;</b>//////////////////////////////////////<br>
</font></tt>
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<a NAME="crossover"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCFF" NOSAVE >
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<b> &nbsp;</b>// 1-point crossover for bitstring<br>
<b> &nbsp;eoBinCrossover&lt;Indi> xover1;</b><br>
<b> &nbsp;</b>// uniform crossover for bitstring<br>
<b> &nbsp;eoBinUxOver&lt;Indi> xoverU;</b><br>
<b> &nbsp;</b>// 2-pots xover<br>
<b> &nbsp;eoBinNxOver&lt;Indi> xover2(2);</b><br>
<b> &nbsp;</b>// Combine them with relative rates<br>
<b> &nbsp;eoPropCombinedQuadOp&lt;Indi> xover(xover1, onePointRate);</b><br>
<b> &nbsp;xover.add(xoverU, URate);</b><br>
<b> &nbsp;xover.add(xover2, twoPointsRate, true);</b><br>
</font></tt>
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<b> &nbsp;</b><br>
<b> &nbsp;</b>// standard bit-flip mutation for bitstring<br>
<b> &nbsp;eoBinMutation&lt;Indi> &nbsp;mutationBitFlip(P_MUT_PER_BIT);</b><br>
<b> &nbsp;</b>// mutate exactly 1 bit per individual<br>
<b> &nbsp;eoDetBitFlip&lt;Indi> mutationOneBit; </b><br>
<b> &nbsp;</b>// Combine them with relative rates<br>
<b> &nbsp;eoPropCombinedMonOp&lt;Indi> mutation(mutationBitFlip, bitFlipRate);</b><br>
<b> &nbsp;mutation.add(mutationOneBit, oneBitRate, true);</b><br>
<b> &nbsp;</b><br>
<a NAME="transform"></a>
<b> &nbsp;</b>// The operators are &nbsp;encapsulated into an eoTRansform object<br>
<b> &nbsp;eoSGATransform&lt;Indi> transform(xover, CROSS_RATE, mutation, MUT_RATE);</b><br>
</font></tt>
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</font></tt>
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<b> &nbsp;</b>//////////////////////////////////////<br>
<b> &nbsp;</b>// termination conditions: use more than one<br>
<b> &nbsp;</b>/////////////////////////////////////<br>
<b> &nbsp;</b>// stop after MAX_GEN generations<br>
<b> &nbsp;eoGenContinue&lt;Indi> genCont(MAX_GEN);</b><br>
<b> &nbsp;</b>// do MIN_GEN gen., then stop after STEADY_GEN gen. without improvement<br>
<b> &nbsp;eoSteadyFitContinue&lt;Indi> steadyCont(MIN_GEN, STEADY_GEN);</b><br>
<b> &nbsp;</b>// stop when fitness reaches a target (here VEC_SIZE)<br>
<b> &nbsp;eoFitContinue&lt;Indi> fitCont(0);</b><br>
<b> &nbsp;</b>// do stop when one of the above says so<br>
<b> &nbsp;eoCombinedContinue&lt;Indi> continuator(genCont);</b><br>
<b> &nbsp;continuator.add(steadyCont);</b><br>
<b> &nbsp;continuator.add(fitCont);</b><br>
</font></tt>
</td>
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<b> &nbsp;</b>/////////////////////////////////////////<br>
<b> &nbsp;</b>// the algorithm<br>
<b> &nbsp;</b>////////////////////////////////////////<br>
<b> &nbsp;</b>// Easy EA requires <br>
<b> &nbsp;</b>// selection, transformation, eval, replacement, and stopping criterion<br>
<b> &nbsp;eoEasyEA&lt;Indi> gga(continuator, eval, select, transform, replace);</b><br>
<b> &nbsp;</b>// Apply algo to pop - that's it!<br>
<b> &nbsp;gga(pop);</b><br>
<b> &nbsp;</b><br>
</font></tt>
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<b> &nbsp;</b>// Print (sorted) intial population<br>
<b> &nbsp;pop.sort();</b><br>
<b> &nbsp;cout &lt;&lt; "FINAL Population\n" &lt;&lt; pop &lt;&lt; endl;</b><br>
</font></tt>
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<b>}</b><br>
// A main that catches the exceptions<br>
<b>int main(int argc, char **argv)</b><br>
<b>{</b><br>
<b>#ifdef _MSC_VER</b><br>
<b> &nbsp;</b>// &nbsp;rng.reseed(42);<br>
<b> &nbsp; &nbsp; &nbsp;int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp;flag |= _CRTDBG_LEAK_CHECK_DF;</b><br>
<b> &nbsp; &nbsp; &nbsp;_CrtSetDbgFlag(flag);</b><br>
// &nbsp; &nbsp;_CrtSetBreakAlloc(100);<br>
<b>#endif</b><br>
<b> &nbsp; &nbsp; &nbsp;try</b><br>
<b> &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;main_function(argc, argv);</b><br>
<b> &nbsp; &nbsp; &nbsp;}</b><br>
<b> &nbsp; &nbsp; &nbsp;catch(exception& e)</b><br>
<b> &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;cout &lt;&lt; "Exception: " &lt;&lt; e.what() &lt;&lt; '\n';</b><br>
<b> &nbsp; &nbsp; &nbsp;}</b><br>
<b> &nbsp; &nbsp; &nbsp;return 1;</b><br>
<b>}</b><br>
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//-----------------------------------------------------------------------------<br>
// FirstBitGA.cpp<br>
//-----------------------------------------------------------------------------<br>
//*<br>
// An instance of a VERY simple Bitstring Genetic Algorithm<br>
//<br>
//-----------------------------------------------------------------------------<br>
// standard includes<br>
<b>#include &lt;stdexcept> &nbsp;</b>// runtime_error <br>
<b>#include &lt;iostream> &nbsp; &nbsp;</b>// cout<br>
<b>#include &lt;strstream> &nbsp;</b>// ostrstream, istrstream<br>
// the general include for eo<br>
<b>#include &lt;eo></b><br>
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//-----------------------------------------------------------------------------<br>
// define your individuals<br>
<b>typedef eoBin&lt;double> Indi; &nbsp; &nbsp; &nbsp; &nbsp;</b>// A bitstring with fitness double<br>
</font></tt>
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//-----------------------------------------------------------------------------<br>
// a simple fitness function that computes the number of ones of a bitstring<br>
// &nbsp;@param _indi A biststring individual<br>
<a name="evalfunc"></a>
<b>double binary_value(const Indi & _indi)</b><br>
<b>{</b><br>
<b> &nbsp;double sum = 0;</b><br>
<b> &nbsp;for (unsigned i = 0; i &lt; _indi.size(); i++)</b><br>
<b> &nbsp; &nbsp; &nbsp;sum += _indi[i];</b><br>
<b> &nbsp;return sum;</b><br>
<b>}</b><br>
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//-----------------------------------------------------------------------------<br>
<b>void main_function(int argc, char **argv)</b><br>
<b>{</b><br>
</font></tt>
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<b> &nbsp;</b>// all parameters are hard-coded!<br>
<b> &nbsp;const unsigned int SEED = 42; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// seed for random number generator<br>
<b> &nbsp;const unsigned int T_SIZE = 3; &nbsp; &nbsp; &nbsp; &nbsp;</b>// size for tournament selection<br>
<b> &nbsp;const unsigned int VEC_SIZE = 8; &nbsp; &nbsp;</b>// Number of bits in genotypes<br>
<b> &nbsp;const unsigned int POP_SIZE = 20; &nbsp;</b>// Size of population<br>
<b> &nbsp;const unsigned int MAX_GEN = 100; &nbsp;</b>// Maximum number of generation before STOP<br>
<b> &nbsp;const float CROSS_RATE = 0.8; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// Crossover rate<br>
<b> &nbsp;const double P_MUT_PER_BIT = 0.01; </b>// probability of bit-flip mutation<br>
<b> &nbsp;const float MUT_RATE = 1.0; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// mutation rate<br>
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<a NAME="random"></a>
<b> &nbsp;</b>//////////////////////////<br>
<b> &nbsp;</b>// &nbsp;Random seed<br>
<b> &nbsp;</b>//////////////////////////<br>
<b> &nbsp;</b>//reproducible random seed: if you don't change SEED above, <br>
<b> &nbsp;</b>// you'll aways get the same result, NOT a random run<br>
<b> &nbsp;rng.reseed(SEED);</b><br>
</font></tt>
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<b> &nbsp;</b>/////////////////////////////<br>
<b> &nbsp;</b>// Fitness function<br>
<b> &nbsp;</b>////////////////////////////<br>
<b> &nbsp;</b>// Evaluation: from a plain C++ fn to an EvalFunc Object<br>
<b> &nbsp;eoEvalFuncPtr&lt;Indi> eval( &nbsp;binary_value );</b><br>
</font></tt>
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<b> &nbsp;</b>////////////////////////////////<br>
<b> &nbsp;</b>// Initilisation of population<br>
<b> &nbsp;</b>////////////////////////////////<br>
<b> &nbsp;</b>// declare the population<br>
<b> &nbsp;eoPop&lt;Indi> pop;</b><br>
<b> &nbsp;</b>// fill it!<br>
<b> &nbsp;for (unsigned int igeno=0; igeno&lt;POP_SIZE; igeno++)</b><br>
<b> &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Indi v; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// void individual, to be filled<br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;for (unsigned ivar=0; ivar&lt;VEC_SIZE; ivar++)</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;bool r = rng.flip(); </b>// new value, random in {0,1}<br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;v.push_back(r); &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// append that random value to v<br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;}</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;eval(v); &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// evaluate it<br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;pop.push_back(v); &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// and put it in the population<br>
<b> &nbsp; &nbsp; &nbsp;}</b><br>
</font></tt>
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<b> &nbsp;</b>// sort pop before printing it!<br>
<b> &nbsp;pop.sort();</b><br>
<b> &nbsp;</b>// Print (sorted) intial population (raw printout)<br>
<b> &nbsp;cout &lt;&lt; "Initial Population" &lt;&lt; endl;</b><br>
<b> &nbsp;cout &lt;&lt; pop;</b><br>
</font></tt>
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<b> &nbsp;</b>/////////////////////////////////////<br>
<b> &nbsp;</b>// selection and replacement<br>
<b> &nbsp;</b>////////////////////////////////////<br>
</font></tt>
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<b> &nbsp;</b>// The robust tournament selection<br>
<b> &nbsp;eoDetTournament&lt;Indi> select(T_SIZE); &nbsp;</b>// T_SIZE in [2,POP_SIZE]<br>
</font></tt>
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<b> &nbsp;</b>// The simple GA evolution engine uses generational replacement<br>
<b> &nbsp;</b>// so no replacement procedure is needed<br>
</font></tt>
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</font></tt>
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<b> &nbsp;</b>//////////////////////////////////////<br>
<b> &nbsp;</b>// The variation operators<br>
<b> &nbsp;</b>//////////////////////////////////////<br>
</font></tt>
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<b> &nbsp;</b>// 1-point mutation for bitstring<br>
<b> &nbsp;eoBinCrossover&lt;Indi> xover;</b><br>
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<b> &nbsp;</b><br>
<b> &nbsp;</b>// standard bit-flip mutation for bitstring<br>
<b> &nbsp;eoBinMutation&lt;Indi> &nbsp;mutation(P_MUT_PER_BIT);</b><br>
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<b> &nbsp;</b>//////////////////////////////////////<br>
<b> &nbsp;</b>// termination condition<br>
<b> &nbsp;</b>/////////////////////////////////////<br>
<b> &nbsp;</b>// stop after MAX_GEN generations<br>
<b> &nbsp;eoGenContinue&lt;Indi> continuator(MAX_GEN);</b><br>
<b> &nbsp;</b><br>
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<b> &nbsp;</b>/////////////////////////////////////////<br>
<b> &nbsp;</b>// the algorithm<br>
<b> &nbsp;</b>////////////////////////////////////////<br>
<b> &nbsp;</b>// standard Generational GA requires as parameters<br>
<b> &nbsp;</b>// selection, evaluation, crossover and mutation, stopping criterion<br>
<b> </b><br>
<b> &nbsp;eoSGA&lt;Indi> gga(select, xover, CROSS_RATE, mutation, MUT_RATE, </b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;eval, continuator);</b><br>
<b> &nbsp;</b>// Apply algo to pop - that's it!<br>
<b> &nbsp;gga(pop);</b><br>
<b> &nbsp;</b><br>
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<b> &nbsp;</b>// Print (sorted) intial population<br>
<b> &nbsp;pop.sort();</b><br>
<b> &nbsp;cout &lt;&lt; "FINAL Population\n" &lt;&lt; pop &lt;&lt; endl;</b><br>
</font></tt>
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<b>}</b><br>
<b> </b>// A main that catches the exceptions<br>
<b>int main(int argc, char **argv)</b><br>
<b>{</b><br>
<b>#ifdef _MSC_VER</b><br>
<b> &nbsp;</b>// &nbsp;rng.reseed(42);<br>
<b> &nbsp; &nbsp; &nbsp;int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp;flag |= _CRTDBG_LEAK_CHECK_DF;</b><br>
<b> &nbsp; &nbsp; &nbsp;_CrtSetDbgFlag(flag);</b><br>
// &nbsp; &nbsp;_CrtSetBreakAlloc(100);<br>
<b>#endif</b><br>
<b> &nbsp; &nbsp; &nbsp;try</b><br>
<b> &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;main_function(argc, argv);</b><br>
<b> &nbsp; &nbsp; &nbsp;}</b><br>
<b> &nbsp; &nbsp; &nbsp;catch(exception& e)</b><br>
<b> &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;cout &lt;&lt; "Exception: " &lt;&lt; e.what() &lt;&lt; '\n';</b><br>
<b> &nbsp; &nbsp; &nbsp;}</b><br>
<b> &nbsp; &nbsp; &nbsp;return 1;</b><br>
<b>}</b><br>
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<table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCC99" NOSAVE >
<tr NOSAVE>
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//-----------------------------------------------------------------------------<br>
// FirstRealEA.cpp<br>
//-----------------------------------------------------------------------------<br>
//*<br>
// Still an instance of a VERY simple Real-coded &nbsp;Genetic Algorithm <br>
// (see FirstBitGA.cpp) but now with &nbsp;Breeder - and Combined Ops<br>
//<br>
//-----------------------------------------------------------------------------<br>
// standard includes<br>
<b>#include &lt;stdexcept> &nbsp;</b>// runtime_error <br>
<b>#include &lt;iostream> &nbsp; &nbsp;</b>// cout<br>
<b>#include &lt;strstream> &nbsp;</b>// ostrstream, istrstream<br>
// the general include for eo<br>
<b>#include &lt;eo></b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="representation"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFFFCC" NOSAVE >
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<td>
<tt><font color="#999900">
//-----------------------------------------------------------------------------<br>
// define your individuals<br>
<b>typedef eoReal&lt;double> Indi; </b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="evalfunc"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCCC" NOSAVE >
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<td>
<tt><font color="#CC0000">
//-----------------------------------------------------------------------------<br>
// a simple fitness function that computes the euclidian norm of a real vector<br>
// Now in a separate file, and declared as binary_value(const vector&lt;bool> &)<br>
<b>#include "real_value.h"</b><br>
</font></tt>
</td>
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</table>
<a NAME="general"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCC99" NOSAVE >
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<tt><font color="#993300">
//-----------------------------------------------------------------------------<br>
<b>void main_function(int argc, char **argv)</b><br>
<b>{</b><br>
</font></tt>
</td>
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<a NAME="parametres"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#CCFFFF" NOSAVE >
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<tt><font color="#3366FF">
<b> &nbsp;const unsigned int SEED = 42; </b>// seed for random number generator<br>
<b> &nbsp;const unsigned int T_SIZE = 3; </b>// size for tournament selection<br>
<b> &nbsp;const unsigned int VEC_SIZE = 8; </b>// Number of object variables in genotypes<br>
<b> &nbsp;const unsigned int POP_SIZE = 20; </b>// Size of population<br>
<b> &nbsp;const unsigned int MAX_GEN = 500; </b>// Maximum number of generation before STOP<br>
<b> &nbsp;const unsigned int MIN_GEN = 10; &nbsp;</b>// Minimum number of generation before ...<br>
<b> &nbsp;const unsigned int STEADY_GEN = 50; </b>// stop after STEADY_GEN gen. without improvelent<br>
<b> &nbsp;const float P_CROSS = 0.8; </b>// Crossover probability<br>
<b> &nbsp;const float P_MUT = 0.5; </b>// mutation probability<br>
<b> &nbsp;const double EPSILON = 0.01; </b>// range for real uniform mutation<br>
<b> &nbsp;</b>// some parameters for chosing among different operators<br>
<b> &nbsp;const double segmentRate = 0.5; &nbsp; &nbsp; &nbsp; &nbsp;</b>// rate for 1-pt Xover<br>
<b> &nbsp;const double arithmeticRate = 0.5; &nbsp; &nbsp; &nbsp; &nbsp;</b>// rate for 2-pt Xover<br>
<b> &nbsp;const double uniformMutRate = 0.5; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// rate for bit-flip mutation<br>
<b> &nbsp;const double detMutRate = 0.5; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// rate for one-bit mutation<br>
</font></tt>
</td>
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<a NAME="general"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCC99" NOSAVE >
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<tt><font color="#993300">
<b> &nbsp;</b>//////////////////////////<br>
<b> &nbsp;</b>// &nbsp;Random seed<br>
<b> &nbsp;</b>//////////////////////////<br>
<b> &nbsp;</b>//reproducible random seed: if you don't change SEED above, <br>
<b> &nbsp;</b>// you'll aways get the same result, NOT a random run<br>
<b> &nbsp;rng.reseed(SEED);</b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="eval"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCCC" NOSAVE >
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<td>
<tt><font color="#CC0000">
<b> &nbsp;</b>/////////////////////////////<br>
<b> &nbsp;</b>// Fitness function<br>
<b> &nbsp;</b>////////////////////////////<br>
<b> &nbsp;</b>// Evaluation: from a plain C++ fn to an EvalFunc Object<br>
<b> &nbsp;</b>// you need to give the full description of the function<br>
<b> &nbsp;eoEvalFuncPtr&lt;Indi, double, const vector&lt;double>& > eval( &nbsp;real_value );</b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="init"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCFF" NOSAVE >
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<tt><font color="#993399">
<b> &nbsp;</b>////////////////////////////////<br>
<b> &nbsp;</b>// Initilisation of population<br>
<b> &nbsp;</b>////////////////////////////////<br>
<b> &nbsp;</b>// based on a uniform generator<br>
<b> &nbsp;eoInitFixedLength&lt;Indi, uniform_generator&lt;double> ></b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;random(VEC_SIZE, uniform_generator&lt;double>(-1.0, 1.0));</b><br>
<b> &nbsp; &nbsp;</b>// Initialization of the population<br>
<b> &nbsp;eoPop&lt;Indi> pop(POP_SIZE, random);</b><br>
<b> </b><br>
<b> &nbsp;</b>// and evaluate it in one loop<br>
<b> &nbsp;apply&lt;Indi>(eval, pop); </b>// STL syntax<br>
</font></tt>
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<a NAME="output"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#CCFFFF" NOSAVE >
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<td>
<tt><font color="#3366FF">
<b> &nbsp;</b>// sort pop before printing it!<br>
<b> &nbsp;pop.sort();</b><br>
<b> &nbsp;</b>// Print (sorted) intial population (raw printout)<br>
<b> &nbsp;cout &lt;&lt; "Initial Population" &lt;&lt; endl;</b><br>
<b> &nbsp;cout &lt;&lt; pop;</b><br>
</font></tt>
</td>
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<a NAME="engine"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#99FFCC" NOSAVE >
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<tt><font color="#009900">
<b> &nbsp;</b>/////////////////////////////////////<br>
<b> &nbsp;</b>// selection and replacement<br>
<b> &nbsp;</b>////////////////////////////////////<br>
</font></tt>
</td>
</tr>
</table>
<a NAME="select"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#99FFCC" NOSAVE >
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<td>
<tt><font color="#009900">
<b> &nbsp;</b>// The robust tournament selection<br>
<b> &nbsp;eoDetTournament&lt;Indi> selectOne(T_SIZE);</b><br>
<a NAME="select_encapsulate"></a>
<b> &nbsp;</b>// is now encapsulated in a eoSelectPerc (entage)<br>
<b> &nbsp;eoSelectPerc&lt;Indi> select(selectOne);</b>// by default rate==1<br>
</font></tt>
</td>
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<a NAME="replace"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#99FFCC" NOSAVE >
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<tt><font color="#009900">
<b> &nbsp;</b>// And we now have the full slection/replacement - though with <br>
<b> &nbsp;</b>// no replacement (== generational replacement) at the moment :-)<br>
<b> &nbsp;eoNoReplacement&lt;Indi> replace; </b><br>
</font></tt>
</td>
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</table>
<a NAME="operators"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCFF" NOSAVE >
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<tt><font color="#993399">
<b> &nbsp;</b>//////////////////////////////////////<br>
<b> &nbsp;</b>// The variation operators<br>
<b> &nbsp;</b>//////////////////////////////////////<br>
</font></tt>
</td>
</tr>
</table>
<a NAME="crossover"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCFF" NOSAVE >
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<td>
<tt><font color="#993399">
<b> &nbsp;</b>// uniform chooce on segment made by the parents<br>
<b> &nbsp;eoSegmentCrossover&lt;Indi> xoverS;</b><br>
<b> &nbsp;</b>// uniform choice in hypercube built by the parents<br>
<b> &nbsp;eoArithmeticCrossover&lt;Indi> xoverA;</b><br>
<b> &nbsp;</b>// Combine them with relative rates<br>
<b> &nbsp;eoPropCombinedQuadOp&lt;Indi> xover(xoverS, segmentRate);</b><br>
<b> &nbsp;xover.add(xoverA, arithmeticRate, true);</b><br>
</font></tt>
</td>
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</table>
<a NAME="mutation"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCFF" NOSAVE >
<tr>
<td>
<tt><font color="#993399">
<b> &nbsp;</b><br>
<b> &nbsp;</b>// offspring(i) uniformly chosen in [parent(i)-epsilon, parent(i)+epsilon]<br>
<b> &nbsp;eoUniformMutation&lt;Indi> &nbsp;mutationU(EPSILON); </b><br>
<b> &nbsp;</b>// k (=1) coordinates of parents are uniformly modified<br>
<b> &nbsp;eoDetUniformMutation&lt;Indi> &nbsp;mutationD(EPSILON); </b><br>
<b> &nbsp;</b>// Combine them with relative rates<br>
<b> &nbsp;eoPropCombinedMonOp&lt;Indi> mutation(mutationU, uniformMutRate);</b><br>
<b> &nbsp;mutation.add(mutationD, detMutRate, true);</b><br>
<b> &nbsp;</b><br>
<b> &nbsp;</b>// The operators are &nbsp;encapsulated into an eoTRansform object<br>
<b> &nbsp;eoSGATransform&lt;Indi> transform(xover, P_CROSS, mutation, P_MUT);</b><br>
</font></tt>
</td>
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<a NAME="stop"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#CCFFFF" NOSAVE >
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<td>
<tt><font color="#3366FF">
</font></tt>
</td>
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</table>
<a NAME="checkpoint"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#CCFFFF" NOSAVE >
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<td>
<tt><font color="#3366FF">
<b> &nbsp;</b>//////////////////////////////////////<br>
<b> &nbsp;</b>// termination conditions: use more than one<br>
<b> &nbsp;</b>/////////////////////////////////////<br>
<b> &nbsp;</b>// stop after MAX_GEN generations<br>
<b> &nbsp;eoGenContinue&lt;Indi> genCont(MAX_GEN);</b><br>
<b> &nbsp;</b>// do MIN_GEN gen., then stop after STEADY_GEN gen. without improvement<br>
<b> &nbsp;eoSteadyFitContinue&lt;Indi> steadyCont(MIN_GEN, STEADY_GEN);</b><br>
<b> &nbsp;</b>// stop when fitness reaches a target (here VEC_SIZE)<br>
<b> &nbsp;eoFitContinue&lt;Indi> fitCont(0);</b><br>
<b> &nbsp;</b>// do stop when one of the above says so<br>
<b> &nbsp;eoCombinedContinue&lt;Indi> continuator(genCont);</b><br>
<b> &nbsp;continuator.add(steadyCont);</b><br>
<b> &nbsp;continuator.add(fitCont);</b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="generation"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCC99" NOSAVE >
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<td>
<tt><font color="#FF6666">
<b> &nbsp;</b>/////////////////////////////////////////<br>
<b> &nbsp;</b>// the algorithm<br>
<b> &nbsp;</b>////////////////////////////////////////<br>
<b> &nbsp;</b>// Easy EA requires <br>
<b> &nbsp;</b>// selection, transformation, eval, replacement, and stopping criterion<br>
<b> &nbsp;eoEasyEA&lt;Indi> gga(continuator, eval, select, transform, replace);</b><br>
<b> &nbsp;</b>// Apply algo to pop - that's it!<br>
<b> &nbsp;cout &lt;&lt; "\n &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Here we go\n\n";</b><br>
<b> &nbsp;gga(pop);</b><br>
<b> &nbsp;</b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="output"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#CCFFFF" NOSAVE >
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<td>
<tt><font color="#3366FF">
<b> &nbsp;</b>// Print (sorted) intial population<br>
<b> &nbsp;pop.sort();</b><br>
<b> &nbsp;cout &lt;&lt; "FINAL Population\n" &lt;&lt; pop &lt;&lt; endl;</b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="general"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCC99" NOSAVE >
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<td>
<tt><font color="#993300">
<b>}</b><br>
// A main that catches the exceptions<br>
<b>int main(int argc, char **argv)</b><br>
<b>{</b><br>
<b>#ifdef _MSC_VER</b><br>
<b> &nbsp;</b>// &nbsp;rng.reseed(42);<br>
<b> &nbsp; &nbsp; &nbsp;int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp;flag |= _CRTDBG_LEAK_CHECK_DF;</b><br>
<b> &nbsp; &nbsp; &nbsp;_CrtSetDbgFlag(flag);</b><br>
// &nbsp; &nbsp;_CrtSetBreakAlloc(100);<br>
<b>#endif</b><br>
<b> &nbsp; &nbsp; &nbsp;try</b><br>
<b> &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;main_function(argc, argv);</b><br>
<b> &nbsp; &nbsp; &nbsp;}</b><br>
<b> &nbsp; &nbsp; &nbsp;catch(exception& e)</b><br>
<b> &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;cout &lt;&lt; "Exception: " &lt;&lt; e.what() &lt;&lt; '\n';</b><br>
<b> &nbsp; &nbsp; &nbsp;}</b><br>
<b> &nbsp; &nbsp; &nbsp;return 1;</b><br>
<b>}</b><br>
</font></font></font></td>
</tr>
</table>
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<tr NOSAVE>
<td NOSAVE><tt><font color="#993300">
//-----------------------------------------------------------------------------<br>
// FirstRealGA.cpp<br>
//-----------------------------------------------------------------------------<br>
//*<br>
// An instance of a VERY simple Real-coded Genetic Algorithm<br>
//<br>
//-----------------------------------------------------------------------------<br>
// standard includes<br>
<b>#include &lt;stdexcept> &nbsp;</b>// runtime_error <br>
<b>#include &lt;iostream> &nbsp; &nbsp;</b>// cout<br>
<b>#include &lt;strstream> &nbsp;</b>// ostrstream, istrstream<br>
// the general include for eo<br>
<b>#include &lt;eo></b><br>
</font></tt>
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<tt><font color="#999900">
//-----------------------------------------------------------------------------<br>
// define your individuals<br>
<b> typedef eoReal&lt;double> Indi;</b><br>
</font></tt>
</td>
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<tt><font color="#CC0000">
//-----------------------------------------------------------------------------<br>
// a simple fitness function that computes the euclidian norm of a real vector<br>
// &nbsp; &nbsp; &nbsp;@param _indi A real-valued individual <br>
<a name="evalfunc"></a>
<b>double real_value(const Indi & _indi)</b><br>
<b>{</b><br>
<b> &nbsp;double sum = 0;</b><br>
<b> &nbsp;for (unsigned i = 0; i &lt; _indi.size(); i++)</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;sum += _indi[i]*_indi[i];</b><br>
<b> &nbsp;return (-sum); &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// maximizing only<br>
<b>}</b><br>
</font></tt>
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<tt><font color="#993300">
//-----------------------------------------------------------------------------<br>
<b>void main_function(int argc, char **argv)</b><br>
<b>{</b><br>
</font></tt>
</td>
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<tt><font color="#3366FF">
<b> &nbsp;</b>// all parameters are hard-coded!<br>
<b> &nbsp;const unsigned int SEED = 42; </b>// seed for random number generator<br>
<b> &nbsp;const unsigned int VEC_SIZE = 8; </b>// Number of object variables in genotypes<br>
<b> &nbsp;const unsigned int POP_SIZE = 20; </b>// Size of population<br>
<b> &nbsp;const unsigned int T_SIZE = 3; </b>// size for tournament selection<br>
<b> &nbsp;const unsigned int MAX_GEN = 500; </b>// Maximum number of generation before STOP<br>
<b> &nbsp;const float CROSS_RATE = 0.8; </b>// Crossover rate<br>
<b> &nbsp;const double EPSILON = 0.01; &nbsp;</b>// range for real uniform mutation<br>
<b> &nbsp;const float MUT_RATE = 0.5; &nbsp; &nbsp;</b>// mutation rate<br>
</font></tt>
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<tt><font color="#993300">
<a NAME="random"></a>
<b> &nbsp;</b>//////////////////////////<br>
<b> &nbsp;</b>// &nbsp;Random seed<br>
<b> &nbsp;</b>//////////////////////////<br>
<b> &nbsp;</b>//reproducible random seed: if you don't change SEED above, <br>
<b> &nbsp;</b>// you'll aways get the same result, NOT a random run<br>
<b> &nbsp;rng.reseed(SEED);</b><br>
</font></tt>
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<a NAME="eval"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCCC" NOSAVE >
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<tt><font color="#CC0000">
<b> &nbsp;</b>/////////////////////////////<br>
<b> &nbsp;</b>// Fitness function<br>
<b> &nbsp;</b>////////////////////////////<br>
<b> &nbsp;</b>// Evaluation: from a plain C++ fn to an EvalFunc Object<br>
<b> &nbsp;eoEvalFuncPtr&lt;Indi> eval( &nbsp;real_value );</b><br>
</font></tt>
</td>
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<a NAME="init"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCFF" NOSAVE >
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<tt><font color="#993399">
<b> &nbsp;</b>////////////////////////////////<br>
<b> &nbsp;</b>// Initilisation of population<br>
<b> &nbsp;</b>////////////////////////////////<br>
<b> &nbsp;</b>// declare the population<br>
<b> &nbsp;eoPop&lt;Indi> pop;</b><br>
<b> &nbsp;</b>// fill it!<br>
<b> &nbsp;for (unsigned int igeno=0; igeno&lt;POP_SIZE; igeno++)</b><br>
<b> &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;Indi v; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// void individual, to be filled<br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;for (unsigned ivar=0; ivar&lt;VEC_SIZE; ivar++)</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;double r = 2*rng.uniform() - 1; </b>// new value, random in [-1,1)<br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;v.push_back(r); &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// append that random value to v<br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;}</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;eval(v); &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// evaluate it<br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;pop.push_back(v); &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// and put it in the population<br>
<b> &nbsp; &nbsp; &nbsp;}</b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="output"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#CCFFFF" NOSAVE >
<tr>
<td>
<tt><font color="#3366FF">
<b> &nbsp;</b>// sort pop before printing it!<br>
<b> &nbsp;pop.sort();</b><br>
<b> &nbsp;</b>// Print (sorted) intial population (raw printout)<br>
<b> &nbsp;cout &lt;&lt; "Initial Population" &lt;&lt; endl;</b><br>
<b> &nbsp;cout &lt;&lt; pop;</b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="engine"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#99FFCC" NOSAVE >
<tr>
<td>
<tt><font color="#009900">
<b> &nbsp;</b>/////////////////////////////////////<br>
<b> &nbsp;</b>// selection and replacement<br>
<b> &nbsp;</b>////////////////////////////////////<br>
</font></tt>
</td>
</tr>
</table>
<a NAME="select"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#99FFCC" NOSAVE >
<tr>
<td>
<tt><font color="#009900">
<b> &nbsp;</b>// The robust tournament selection<br>
<b> &nbsp;eoDetTournament&lt;Indi> select(T_SIZE); &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</b>// T_SIZE in [2,POP_SIZE]<br>
</font></tt>
</td>
</tr>
</table>
<a NAME="replace"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#99FFCC" NOSAVE >
<tr>
<td>
<tt><font color="#009900">
<b> &nbsp;</b>// eoSGA uses generational replacement by default<br>
<b> &nbsp;</b>// so no replacement procedure has to be given<br>
</font></tt>
</td>
</tr>
</table>
<a NAME="stop"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#CCFFFF" NOSAVE >
<tr>
<td>
<tt><font color="#3366FF">
</font></tt>
</td>
</tr>
</table>
<a NAME="checkpoint"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#CCFFFF" NOSAVE >
<tr>
<td>
<tt><font color="#3366FF">
<b> &nbsp;</b>//////////////////////////////////////<br>
<b> &nbsp;</b>// termination condition<br>
<b> &nbsp;</b>/////////////////////////////////////<br>
<b> &nbsp;</b>// stop after MAX_GEN generations<br>
<b> &nbsp;eoGenContinue&lt;Indi> continuator(MAX_GEN);</b><br>
<b> &nbsp;</b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="operators"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCFF" NOSAVE >
<tr>
<td>
<tt><font color="#993399">
<b> &nbsp;</b>//////////////////////////////////////<br>
<b> &nbsp;</b>// The variation operators<br>
<b> &nbsp;</b>//////////////////////////////////////<br>
</font></tt>
</td>
</tr>
</table>
<a NAME="mutation"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCFF" NOSAVE >
<tr>
<td>
<tt><font color="#993399">
<b> &nbsp;</b>// offspring(i) uniformly chosen in [parent(i)-epsilon, parent(i)+epsilon]<br>
<b> &nbsp;eoUniformMutation&lt;Indi> &nbsp;mutation(EPSILON); </b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="crossover"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCCFF" NOSAVE >
<tr>
<td>
<tt><font color="#993399">
<b> &nbsp;</b>// offspring(i) is a linear combination of parent(i)<br>
<b> &nbsp;eoArithmeticCrossover&lt;Indi> xover;</b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="generation"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCC99" NOSAVE >
<tr>
<td>
<tt><font color="#FF6666">
<b> &nbsp;</b>/////////////////////////////////////////<br>
<b> &nbsp;</b>// the algorithm<br>
<b> &nbsp;</b>////////////////////////////////////////<br>
<b> &nbsp;</b>// standard Generational GA requires<br>
<b> &nbsp;</b>// selection, evaluation, crossover and mutation, stopping criterion<br>
<b> </b><br>
<b> &nbsp;eoSGA&lt;Indi> gga(select, xover, CROSS_RATE, mutation, MUT_RATE, </b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;eval, continuator);</b><br>
<b> &nbsp;</b>// Apply algo to pop - that's it!<br>
<b> &nbsp;gga(pop);</b><br>
<b> &nbsp;</b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="final_output"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#CCFFFF" NOSAVE >
<tr>
<td>
<tt><font color="#3366FF">
<b> &nbsp;</b>// Print (sorted) intial population<br>
<b> &nbsp;pop.sort();</b><br>
<b> &nbsp;cout &lt;&lt; "FINAL Population\n" &lt;&lt; pop &lt;&lt; endl;</b><br>
</font></tt>
</td>
</tr>
</table>
<a NAME="main"></a><table BORDER=0 CELLSPACING=0 COLS=1 WIDTH="100%" BGCOLOR="#FFCC99" NOSAVE >
<tr>
<td>
<tt><font color="#993300">
<b>}</b><br>
// A main that catches the exceptions<br>
<b>int main(int argc, char **argv)</b><br>
<b>{</b><br>
<b>#ifdef _MSC_VER</b><br>
<b> &nbsp;</b>// &nbsp;rng.reseed(42);<br>
<b> &nbsp; &nbsp; &nbsp;int flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp;flag |= _CRTDBG_LEAK_CHECK_DF;</b><br>
<b> &nbsp; &nbsp; &nbsp;_CrtSetDbgFlag(flag);</b><br>
// &nbsp; &nbsp;_CrtSetBreakAlloc(100);<br>
<b>#endif</b><br>
<b> &nbsp; &nbsp; &nbsp;try</b><br>
<b> &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;main_function(argc, argv);</b><br>
<b> &nbsp; &nbsp; &nbsp;}</b><br>
<b> &nbsp; &nbsp; &nbsp;catch(exception& e)</b><br>
<b> &nbsp; &nbsp; &nbsp;{</b><br>
<b> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;cout &lt;&lt; "Exception: " &lt;&lt; e.what() &lt;&lt; '\n';</b><br>
<b> &nbsp; &nbsp; &nbsp;}</b><br>
<b> &nbsp; &nbsp; &nbsp;return 1;</b><br>
<b>}</b><br>
</font></font></font></td>
</tr>
</table>
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<center>
<h1>
<font color="#FF0000">A First Real GA</font></h1></center>
Click on the figure to see the corresponding code. Tutorial comments are
in variable length fonts, after the code.
<center>
<p><img SRC="EA_tutorial.jpg" USEMAP="#Map" ></center>
<map NAME="Map"><area SHAPE="rect" HREF="#init" COORDS="0,0,112,40"><area SHAPE="rect" HREF="#eval" COORDS="0,78,112,112"><area SHAPE="rect" HREF="#select" COORDS="395,70,507,107"><area SHAPE="rect" HREF="#replace" COORDS="145,144,253,182"><area SHAPE="rect" HREF="#crossover" COORDS="433,145,543,164"><area SHAPE="rect" HREF="#mutation" COORDS="433,164,543,182"><area SHAPE="rect" HREF="#eval" COORDS="218,217,325,252"><area SHAPE="rect" HREF="#output" COORDS="235,14,415,38"><area SHAPE="rect" HREF="#representation" COORDS="143,68,253,114"><area SHAPE="rect" HREF="#representation" COORDS="394,214,515,255"><area SHAPE="rect" HREF="#stop" COORDS="278,74,370,109"><area SHAPE="rect" HREF="#generation" COORDS="257,114,431,213"><!-- 4 lignes en bas --><area SHAPE="rect" HREF="#eval" COORDS="0,334,207,352"><area SHAPE="rect" HREF="#engine" COORDS="0,310,356,334"><area SHAPE="rect" HREF="#operators" COORDS="0,288,230,310"><area SHAPE="rect" HREF="#representation" COORDS="230,288,450,310"><area SHAPE="rect" HREF="#parametres" COORDS="0,358,278,378"></map>
<p><font face="Courier New,Courier"><font size=+1>//-----------------------------------------------------------------------------</font></font>
<p><font face="Courier New,Courier"><font color="#993300"><font size=+1>#include
&lt;stdexcept > // runtime_error</font></font></font>
<p><font face="Courier New,Courier"><font size=+1>//-----------------------------------------------------------------------------</font></font>
<br><font face="Courier New,Courier"><font size=+1>// FirstRealGA.cpp</font></font>
<br><font face="Courier New,Courier"><font size=+1>//-----------------------------------------------------------------------------</font></font>
<br><font face="Courier New,Courier"><font size=+1>//*</font></font>
<br><font face="Courier New,Courier"><font size=+1>// An instance of a
VERY simple Real-coded Genetic Algorithm</font></font>
<br><font face="Courier New,Courier"><font size=+1>//</font></font>
<br><font face="Courier New,Courier"><font size=+1>//-----------------------------------------------------------------------------</font></font>
<br><font face="Courier New,Courier"><font size=+1>// standard includes</font></font>
<p><font face="Courier New,Courier"><font color="#993300"><font size=+1>#include
&lt;iostream>// cout</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>#include
&lt;strstream>// ostrstream, istrstream</font></font></font>
<p><font face="Courier New,Courier"><font size=+1>// the general include
for eo</font></font>
<p><font face="Courier New,Courier"><font color="#FF6666"><font size=+1>#include
&lt;eo></font></font></font>
<p><font face="Courier New,Courier"><font size=+1>// specific incluse,
as Real is not (yet) in the standard eo source dir</font></font>
<br><font face="Courier New,Courier"><font color="#FF6666"><font size=+1>#include
"eoeal.h"</font></font></font>
<br><font face="Courier New,Courier"><font color="#FF6666"><font size=+1>#include
"eoRealOp.h"</font></font></font>
<p><font face="Courier New,Courier"><font size=+1>//-----------------------------------------------------------------------------</font></font>
<br><font face="Courier New,Courier"><font size=+1>// define your individual:</font></font>
<p><a NAME="representation"></a><font face="Courier New,Courier"><font color="#FFFF00"><font size=+1>typedef
eoReal&lt;double> Indi;</font></font></font>
<p>You say here that you will be handling <font face="Arial,Helvetica">arrays
of doubles</font>, whose fitness is a double
<br>Note that this makes Indi derive from <a href="eoProgramming.html#STL">STL
class</a> <font color="#993300">vector&lt;double></font>
<br><font face="Courier New,Courier"><font size=+1>//-----------------------------------------------------------------------------</font></font>
<br><font face="Courier New,Courier"><font size=+1>/** a simple fitness
function that computes the euclidian norm of a real vector</font></font>
<br><font face="Courier New,Courier"><font size=+1>&nbsp;&nbsp;&nbsp; @param
_indi A real-valued individual</font></font>
<br><font face="Courier New,Courier"><font size=+1>*/</font></font>
<p><a NAME="evalfunc"></a><font face="Courier New,Courier"><font color="#CC0000"><font size=+1>double
real_value(const Indi &amp; _indi)</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC0000"><font size=+1>{</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC0000"><font size=+1>&nbsp;
double sum = 0;</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC0000"><font size=+1>&nbsp;
for (unsigned i = 0; i &lt; _indi.size(); i++)</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC0000"><font size=+1>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
sum += _indi[i]*_indi[i];</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC0000"><font size=+1>&nbsp;
return (-sum);&nbsp;&nbsp; // maximizing</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC0000"><font size=+1>}</font></font></font>
<p>This simple function computes the sum of the squares of the variables
(remember Indi is here a vector of doubles)
<br><font face="Courier New,Courier"><font size=+1>//-----------------------------------------------------------------------------</font></font>
<p><font face="Courier New,Courier"><font color="#993300"><font size=+1>void
main_function(int argc, char **argv)</font></font></font>
<br><font face="Courier New,Courier"><font size=+1>{</font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>const
unsigned int SEED = 42;// seed for random number generator</font></font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>const
unsigned int VEC_SIZE = 8; // Number of object variables in genotypes</font></font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>const
unsigned int POP_SIZE = 20; // Size of population</font></font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>const
unsigned int T_SIZE = 3; // size for tournament selection</font></font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>const
unsigned int MAX_GEN = 500; // Maximum number of generation before STOP</font></font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>const
float CROSS_RATE = 0.8; // Crossover rate</font></font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>const
double EPSILON = 0.01; // range for real uniform mutation</font></font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>const
float MUT_RATE = 0.5; // mutation rate</font></font></font>
<br>&nbsp;
<p><font face="Courier New,Courier"><font size=+1>//////////////////////////</font></font>
<br><font face="Courier New,Courier"><font size=+1>// Random seed</font></font>
<br><font face="Courier New,Courier"><font size=+1>//////////////////////////</font></font>
<br><font face="Courier New,Courier"><font size=+1>//reproducible random
seed: if you don't change SEED above,</font></font>
<br><font face="Courier New,Courier"><font size=+1>// you'll aways get
the same result, NOT a random run</font></font>
<br><font face="Courier New,Courier"><font color="#FF6666"><font size=+1>rng.reseed(SEED);</font></font></font>
<p><font face="Courier New,Courier"><font size=+1>/////////////////////////////</font></font>
<br><font face="Courier New,Courier"><font size=+1>// Fitness function</font></font>
<br><font face="Courier New,Courier"><font size=+1>////////////////////////////</font></font>
<br><font face="Courier New,Courier"><font size=+1>// Evaluation: from
a plain C++ fn to an EvalFunc Object</font></font>
<br><a NAME="eval"></a><font face="Courier New,Courier"><font color="#CC0000"><font size=+1>eoEvalFuncPtr&lt;Indi>
eval( <a href="#evalfunc">real_value</a> );</font></font></font>
<p>This encapsulate the C++ function real_value into a <a href="eoProgramming.html#functors">functor
object</a>
<p><font face="Courier New,Courier"><font size=+1>////////////////////////////////</font></font>
<br><font face="Courier New,Courier"><font size=+1>// Initilisation of
population</font></font>
<br><font face="Courier New,Courier"><font size=+1>////////////////////////////////</font></font>
<p><font face="Courier New,Courier"><font size=+1>// declare the population</font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>eoPop&lt;Indi>
pop;</font></font></font>
<p>Declares a <font face="Arial,Helvetica"><a href="doc/html/class_eopop.html">population
object</a>, </font>which is basically an <a href="eoProgramming.html#STL">STL</a>
<tt><font color="#993300"><font size=+1>vector&lt;Indi></font></font></tt>
<p><font face="Courier New,Courier"><font size=+1>// fill it!</font></font>
<br><a NAME="init"></a><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>for
(unsigned int igeno=0; igeno&lt;POP_SIZE; igeno++)</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>&nbsp;
{</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>&nbsp;&nbsp;&nbsp;
Indi v; // generate a random individual</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>&nbsp;&nbsp;&nbsp;
for (unsigned ivar=0; ivar&lt;VEC_SIZE; ivar++)</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
{</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
double r = 2*rng.uniform() - 1; // new value, random in [-1,1)</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
v.push_back(r); //</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
}</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>&nbsp;&nbsp;&nbsp;
eval(v); // evaluate it</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>&nbsp;&nbsp;&nbsp;
pop.push_back(v); // and put it in the population</font></font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>&nbsp;
}</font></font></font>
<p>This initialization of the population is straightforward
<br><font color="#CC33CC">rng.uniform()</font> generates a double <font face="Arial,Helvetica"><a href="doc/html/class_eorng.html">uniformly
in [0,1)</a>,</font>
<br><font color="#CC33CC">v.push_back</font> simply appends its argument
at the end of <a href="eoProgramming.html#STL">STL</a> vector <font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>v</font></font></font>
<br><font color="#CC33CC">eval(v)</font>evaluates individal <font color="#CC33CC">v</font>
the <a href="eoProgramming.html#functors">functor way</a>, calling <font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>eval.operator()(v)</font></font></font>
<p><font face="Courier New,Courier"><font size=+1>// sort pop before printing
it!</font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>pop.sort();</font></font></font>
<p><font face="Courier New,Courier"><font size=+1>// Print (sorted) intial
population (raw printout)</font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>cout
&lt;&lt; "Initial Population" &lt;&lt; endl;</font></font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>cout
&lt;&lt; pop;</font></font></font>
<p>If you looked at <font face="Arial,Helvetica"><a href="doc/html/class_eopop.html">eoPop</a></font>
inheritance diagram, you noticed that it derives from <font face="Arial,Helvetica"><a href="doc/html/class_eoprintable.html">eoPrintable</a>:</font>
hence you can stream them using the &lt;&lt; operator. Of course, Indis
are <font face="Arial,Helvetica"><a href="doc/html/class_eo.html">EO objects</a>
</font>, which also are eoPrintable, and the &lt;&lt; operator for eoPop
uses the &lt;&lt; operator for Indi.
<p><font face="Courier New,Courier"><font size=+1>/////////////////////////////////////</font></font>
<br><a NAME="engine"></a><font face="Courier New,Courier"><font size=+1>//
selection and replacement</font></font>
<br><font face="Courier New,Courier"><font size=+1>////////////////////////////////////</font></font>
<br><font face="Courier New,Courier"><font size=+1>// The well-known roulette
selection</font></font>
<br><a NAME="select"></a><font face="Courier New,Courier"><font size=+1>//
The robust tournament selection</font></font>
<br><font face="Courier New,Courier"><font color="#009900"><font size=+1>eoDetTournament&lt;Indi>
select(T_SIZE); // SIZE in [2,POP_SIZE]</font></font></font>
<p><a NAME="replace"></a><font face="Courier New,Courier"><font size=+1>//
eoSGA uses <font color="#009900">generational replacement</font> by default</font></font>
<br><font face="Courier New,Courier"><font size=+1>// so no replacement
procedure has to be given</font></font>
<p><font face="Courier New,Courier"><font size=+1>//////////////////////////////////////</font></font>
<br><font face="Courier New,Courier"><font size=+1>// termination condition</font></font>
<br><font face="Courier New,Courier"><font size=+1>/////////////////////////////////////</font></font>
<br><font face="Courier New,Courier"><font size=+1>// stop after MAX_GEN
generations</font></font>
<br><a NAME="stop"></a><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>eoGenContinue&lt;Indi>
continuator(MAX_GEN);</font></font></font>
<p>This class is called <font face="Arial,Helvetica"><a href="doc/html/class_eogencontinue.html">eoGenContinue</a>
</font>because the main loop of all <font face="Arial,Helvetica"><a href="doc/html/class_eoalgo.html">eoAlgo</a>
</font>says ... while continuator(pop)
<p><font face="Courier New,Courier"><font size=+1>//////////////////////////////////////</font></font>
<br><a NAME="operators"></a><font face="Courier New,Courier"><font size=+1>//
The variation operators</font></font>
<br><font face="Courier New,Courier"><font size=+1>//////////////////////////////////////</font></font>
<p><a NAME="mutation"></a><font face="Courier New,Courier"><font size=+1>//
offspring(i) uniformly chosen in [parent(i)-epsilon, parent(i)+epsilon]</font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>eoUniformMutation&lt;Indi>&nbsp;
mutation(EPSILON);</font></font></font>
<br><a NAME="crossover"></a><font face="Courier New,Courier"><font size=+1>//
offspring(i) is a linear combination of parent(i)</font></font>
<br><font face="Courier New,Courier"><font color="#CC33CC"><font size=+1>eoArithmeticCrossover&lt;Indi>
xover;</font></font></font>
<p>The <a href="eoOperators.html">variation operators</a> are respectively
an <font face="Arial,Helvetica"><a href="doc/html/class_eomonop.html">eoMonOp</a></font>
(unary operator) and an <font face="Arial,Helvetica"><a href="doc/html/class_eoquadraticop.html">eoQuadOp</a></font>
(binary operator that modifies both its arguments).
<p><font face="Courier New,Courier"><font size=+1>/////////////////////////////////////////</font></font>
<br><font face="Courier New,Courier"><font size=+1>// the algorithm</font></font>
<br><font face="Courier New,Courier"><font size=+1>////////////////////////////////////////</font></font>
<br><font face="Courier New,Courier"><font size=+1>// standard Generational
GA requires</font></font>
<br><font face="Courier New,Courier"><font size=+1>// selection, evaluation,
crossover and mutation, stopping criterion</font></font>
<br>&nbsp;
<p><a NAME="generation"></a><font face="Courier New,Courier"><font color="#FF6666"><font size=+1>eoSGA&lt;Indi>
gga(select, xover, CROSS_RATE, mutation, MUT_RATE,</font></font></font>
<br><font face="Courier New,Courier"><font color="#FF6666"><font size=+1>eval,
continuator);</font></font></font>
<p><font face="Courier New,Courier"><font size=+1>// Apply algo to pop
- that's it!</font></font>
<br><font face="Courier New,Courier"><font color="#FF6666"><font size=+1>gga(pop);</font></font></font>
<p>This simple algorithm of class eoSGA is a <a href="eoProgramming.html#functors">functor
object</a>, and running the algorithm amounts to call the <font color="#993300">operator()</font>
on the initial population!
<p><font face="Courier New,Courier"><font size=+1>// Print (sorted) intial
population (raw printout)</font></font>
<br><a NAME="output"></a><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>pop.sort();</font></font></font>
<br><font face="Courier New,Courier"><font color="#66FFFF"><font size=+1>cout
&lt;&lt; "FINAL Population\n" &lt;&lt; pop &lt;&lt; endl;</font></font></font>
<p>that's it - just print the final population and you're done!!!
<p><font face="Courier New,Courier"><font size=+1>}</font></font>
<p><font face="Courier New,Courier"><font color="#000000"><font size=+1>//
A main that catches the exceptions - do not modify!</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>int
main(int argc, char **argv)</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>{</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>#ifdef
_MSC_VER</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>//
rng.reseed(42);</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>int
flag = _CrtSetDbgFlag(_CRTDBG_LEAK_CHECK_DF);</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>flag
|= _CRTDBG_LEAK_CHECK_DF;</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>_CrtSetDbgFlag(flag);</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>//
_CrtSetBreakAlloc(100);</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>#endif</font></font></font>
<p><font face="Courier New,Courier"><font color="#993300"><font size=+1>try</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>{</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>main_function(argc,
argv);</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>}</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>catch(exception&amp;
e)</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>{</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>cout
&lt;&lt; "Exception: " &lt;&lt; e.what() &lt;&lt; '\n';</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>}</font></font></font>
<p><font face="Courier New,Courier"><font color="#993300"><font size=+1>return
1;</font></font></font>
<br><font face="Courier New,Courier"><font color="#993300"><font size=+1>}</font></font></font>
<p>
<hr WIDTH="100%"><a href="eoLesson1.html">Back to Lesson 1</a> - <a href="eoTutorial.html">Tutorial
main page </a>- <a href="eoTopDown.html">Top-Down page</a> - <a href="eoBottomUp.html">Bottom-up
page</a> - <a href="eoProgramming.html">Programming hints</a> - <font face="Arial,Helvetica"><a href="doc/html/index.html">EO
documentation</a></font>
<hr>
<address>
<a href="mailto:marc@cmapx.polytechnique.fr">Marc Schoenauer</a></address>
<br><!-- Created: Wed Nov 1 07:18:21 CET 2000 --><!-- hhmts start -->Last
modified: Wed Nov 6 17:22:43 CET 2000<!-- hhmts end -->
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