nojhan/paradiseo
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity

Initial version of the tutorial.

Browse source 
Warning: all Makefile's are hand-made, and will only work in Linux
This commit is contained in:
evomarc 2000-11-29 18:19:57 +00:00
commit b8d4e7faef
48 changed files with 9174 additions and 0 deletions
Download patch file Download diff file Expand all files Collapse all files

193
eo/tutorial/Lesson2/FirstBitEA.cpp Normal file
View file

@ -0,0 +1,193 @@
//-----------------------------------------------------------------------------
// 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;
}

188
eo/tutorial/Lesson2/FirstRealEA.cpp Normal file
View file

@ -0,0 +1,188 @@
//-----------------------------------------------------------------------------
// 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;
}

12
eo/tutorial/Lesson2/Makefile Normal file
View file

@ -0,0 +1,12 @@
.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 *~

17
eo/tutorial/Lesson2/binary_value.h Normal file
View file

@ -0,0 +1,17 @@
#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;
}

195
eo/tutorial/Lesson2/exercise3.cpp Normal file
View file

@ -0,0 +1,195 @@
//-----------------------------------------------------------------------------
// 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;
}

18
eo/tutorial/Lesson2/real_value.h Normal file
View file

@ -0,0 +1,18 @@
#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;
}