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add FastGA foundry and eoStandardBitMutation variants

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This commit is contained in:
Johann Dreo 2020-07-05 19:03:22 +02:00
commit efa6567359
11 changed files with 598 additions and 4 deletions
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1
eo/src/eo
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@ -162,6 +162,7 @@
#include "eoForge.h"
#include "eoAlgoFoundry.h"
#include "eoAlgoFoundryEA.h"
#include "eoAlgoFoundryFastGA.h"
#include "eoEvalFoundryEA.h"
//-----------------------------------------------------------------------------

4
eo/src/eoAlgoFoundry.h
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@ -32,7 +32,7 @@
* and hold the link to the encoding. @see eoAlgoFoundryEA
*
* As with eoForgeVector, adding a managed operator
*is done through public member variable's `add` method,
* is done through public member variable's `add` method,
* which takes the class name as template and its constructor's parameters
* as arguments. For example:
* @code
@ -74,7 +74,7 @@ class eoOperatorFoundry : public eoForgeVector< Itf >
* @endcode
*
* In a second step, the operators to be used should be selected
* by indicating their index, just like if the foundry was a array:
* by indicating their index, just like if the foundry was an array:
* @code
* foundry = {0, 1, 2};
* // ^ ^ ^

251
eo/src/eoAlgoFoundryFastGA.h Normal file
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@ -0,0 +1,251 @@
/*
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation;
version 2 of the License.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
© 2020 Thales group
Authors:
Johann Dreo <johann.dreo@thalesgroup.com>
*/
#ifndef _eoAlgoFoundryFastGA_H_
#define _eoAlgoFoundryFastGA_H_
#include <array>
#include <tuple>
#include <limits>
/** A class that assemble an eoEasyEA on the fly, given a combination of available operators.
*
* The foundry should first be set up with sets of operators
* for the main modules of an EA:
* continuators, crossovers, mutations, selection and replacement operators.
*
* This is done through public member variable's `add` method,
* which takes the class name as template and its constructor's parameters
* as arguments. For example:
* @code
* foundry.selectors.add< eoStochTournamentSelect<EOT> >( 0.5 );
* @endcode
*
* @warning If the constructor takes a reference YOU SHOULD ABSOLUTELY wrap it
* in a `std::ref`, or it will silently be passed as a copy,
* which would effectively disable any link between operators.
*
* In a second step, the operators to be used should be selected
* by indicating their index, passing an array of eight elements:
* @code
* foundry.select({0, 1, 2, 3, 4, 5, 6, 7});
* @endcode
*
* @note: by default, the firsts of the eight operators are selected.
*
* If you don't (want to) recall the order of the operators in the encoding,
* you can use the `index()` member, for example:
* @code
* foundry.at(foundry.continuators.index()) = 2; // select the third continuator
* @endcode
*
* Now, you can call the fourdry just like any eoAlgo, by passing it an eoPop:
* @code
* foundry(pop);
* @encode
* It will instantiate the needed operators (only) and the algorithm itself on-the-fly,
* and then run it.
*
* @note: Thanks to the underlying eoOperatorFoundry, not all the added operators are instantiated.
* Every instantiation is deferred upon actual use. That way, you can still reconfigure them
* at any time with `eoForgeOperator::setup`, for example:
* @code
* foundry.selector.at(0).setup(0.5); // using constructor's arguments
* @endcode
*
* @ingroup Foundry
* @ingroup Algorithms
*/
template<class EOT>
class eoAlgoFoundryFastGA : public eoAlgoFoundry<EOT>
{
public:
/** The constructon only take an eval, because all other operators
* are stored in the public containers.
*/
eoAlgoFoundryFastGA( eoInit<EOT> & init, eoEvalFunc<EOT>& eval, size_t max_evals = 10000, size_t max_restarts = std::numeric_limits<size_t>::max() ) :
eoAlgoFoundry<EOT>(8),
continuators(0, true), // Always re-instantiate continuators, because they hold a state.
crossover_rates(1, false),
crossovers(2, false),
mutation_rates(3, false),
mutations(4, false),
selectors(5, false),
pop_sizes(6, false),
replacements(7, false),
_eval(eval),
_init(init),
_max_evals(max_evals),
_max_restarts(max_restarts)
{ }
public:
/* Operators containers @{ */
eoOperatorFoundry< eoContinue<EOT> > continuators;
eoOperatorFoundry< double > crossover_rates;
eoOperatorFoundry< eoQuadOp<EOT> > crossovers;
eoOperatorFoundry< double > mutation_rates;
eoOperatorFoundry< eoMonOp<EOT> > mutations;
eoOperatorFoundry< eoSelectOne<EOT> > selectors;
eoOperatorFoundry< size_t > pop_sizes;
eoOperatorFoundry< eoReplacement<EOT> > replacements;
/* @} */
/** instantiate and call the pre-selected algorithm.
*/
void operator()(eoPop<EOT>& pop)
{
assert(continuators.size() > 0); assert(this->at(continuators.index()) < continuators.size());
assert( crossover_rates.size() > 0); assert(this->at( crossover_rates.index()) < crossover_rates.size());
assert( crossovers.size() > 0); assert(this->at( crossovers.index()) < crossovers.size());
assert( mutation_rates.size() > 0); assert(this->at( mutation_rates.index()) < mutation_rates.size());
assert( mutations.size() > 0); assert(this->at( mutations.index()) < mutations.size());
assert( selectors.size() > 0); assert(this->at( selectors.index()) < selectors.size());
assert( pop_sizes.size() > 0); assert(this->at( pop_sizes.index()) < pop_sizes.size());
assert(replacements.size() > 0); assert(this->at(replacements.index()) < replacements.size());
// Crossover or clone
double cross_rate = this->crossover_rate();
eoProportionalOp<EOT> cross;
// Cross-over that produce only one offspring,
// made by wrapping the quad op (which produce 2 offsprings)
// in a bin op (which ignore the second offspring).
eoQuad2BinOp<EOT> single_cross(this->crossover());
cross.add(single_cross, cross_rate);
eoBinCloneOp<EOT> cross_clone;
cross.add(cross_clone, 1 - cross_rate); // Clone
// Mutation or clone
double mut_rate = this->mutation_rate();
eoProportionalOp<EOT> mut;
mut.add(this->mutation(), mut_rate);
eoMonCloneOp<EOT> mut_clone;
mut.add(mut_clone, 1 - mut_rate); // FIXME TBC
// Apply mutation after cross-over.
eoSequentialOp<EOT> variator;
variator.add(cross,1.0);
variator.add(mut,1.0);
// All variatiors
double lambda = this->pop_size();
eoGeneralBreeder<EOT> breeder(this->selector(), variator, lambda, /*as rate*/false);
// Objective function calls counter
eoEvalCounterThrowException<EOT> eval(_eval, _max_evals);
eoPopLoopEval<EOT> pop_eval(eval);
// Algorithm itself
eoEasyEA<EOT> algo = eoEasyEA<EOT>(this->continuator(), pop_eval, breeder, this->replacement());
// Restart wrapper
eoAlgoPopReset<EOT> reset_pop(_init, pop_eval);
eoGenContinue<EOT> restart_cont(_max_restarts);
eoAlgoRestart<EOT> restart(eval, algo, restart_cont, reset_pop);
try {
restart(pop);
} catch(eoMaxEvalException e) {
// In case some solutions were not evaluated when max eval occured.
eoPopLoopEval<EOT> pop_last_eval(_eval);
pop_last_eval(pop,pop);
}
}
/** Return an approximate name of the selected algorithm.
*
* @note: does not take into account parameters of the operators,
* only show class names.
*/
std::string name()
{
std::ostringstream name;
name << this->at(continuators.index()) << " (" << this->continuator().className() << ") + ";
name << this->at(crossover_rates.index()) << " (" << this->crossover_rate().className() << ") + ";
name << this->at(crossovers.index()) << " (" << this->crossover().className() << ") + ";
name << this->at(mutation_rates.index()) << " (" << this->mutation_rate().className() << ") + ";
name << this->at(mutations.index()) << " (" << this->mutation().className() << ") + ";
name << this->at(selectors.index()) << " (" << this->selector().className() << ") + ";
name << this->at(pop_sizes.index()) << " (" << this->pop_size().className() << ")";
name << this->at(replacements.index()) << " (" << this->replacement().className() << ")";
return name.str();
}
protected:
eoEvalFunc<EOT>& _eval;
eoInit<EOT>& _init;
const size_t _max_evals;
const size_t _max_restarts;
public:
eoContinue<EOT>& continuator()
{
assert(this->at(continuators.index()) < continuators.size());
return continuators.instantiate(this->at(continuators.index()));
}
double& crossover_rate()
{
assert(this->at(crossover_rates.index()) < crossover_rates.size());
return crossover_rates.instantiate(this->at(crossover_rates.index()));
}
eoQuadOp<EOT>& crossover()
{
assert(this->at(crossovers.index()) < crossovers.size());
return crossovers.instantiate(this->at(crossovers.index()));
}
double& mutation_rate()
{
assert(this->at(mutation_rates.index()) < mutation_rates.size());
return mutation_rates.instantiate(this->at(mutation_rates.index()));
}
eoMonOp<EOT>& mutation()
{
assert(this->at(mutations.index()) < mutations.size());
return mutations.instantiate(this->at(mutations.index()));
}
eoSelectOne<EOT>& selector()
{
assert(this->at(selectors.index()) < selectors.size());
return selectors.instantiate(this->at(selectors.index()));
}
size_t& pop_size()
{
assert(this->at(pop_sizes.index()) < pop_sizes.size());
return pop_sizes.instantiate(this->at(pop_sizes.index()));
}
eoReplacement<EOT>& replacement()
{
assert(this->at(replacements.index()) < replacements.size());
return replacements.instantiate(this->at(replacements.index()));
}
};
#endif // _eoAlgoFoundryFastGA_H_

2
eo/src/eoEasyEA.h
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@ -272,6 +272,8 @@ template<class EOT> class eoEasyEA: public eoAlgo<EOT>
replace(_pop, offspring); // after replace, the new pop. is in _pop
std::cout << _pop << std::endl;
if (pSize > _pop.size())
throw eoException("Population shrinking!");
else if (pSize < _pop.size())

3
eo/src/eoMergeReduce.h
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@ -97,7 +97,8 @@ class eoCommaReplacement : public eoMergeReduce<EOT>
virtual void operator()(eoPop<EOT>& _parents, eoPop<EOT>& _offspring)
{
// There must be more offsprings than parents, or else an exception will be raised
assert( _offspring.size() >= _parents.size() );
// Removed this assertion, which do not hold in some special case of singe indivudal algorithms.
//assert( _offspring.size() >= _parents.size() );
eoMergeReduce<EOT>::operator()( _parents, _offspring );
}

7
eo/src/eoOpContainer.h
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@ -106,6 +106,7 @@ public:
for (size_t i = 0; i < rates.size(); ++i) {
_pop.seekp(pos);
do {
// std::clog << "Before:" << _pop.offspring().size() << " offsprings" << std::endl;
if (eo::rng.flip(rates[i])) {
// try
// {
@ -126,6 +127,11 @@ public:
if (!_pop.exhausted())
++_pop;
// std::clog << "After:" << _pop.offspring().size() << " offsprings" << std::endl;
// std::clog << _pop.offspring() << std::endl;
// std::clog << std::endl;
}
while (!_pop.exhausted());
}
@ -155,6 +161,7 @@ public:
try
{
// std::clog << "\t" << ops[i]->className() << std::endl;
(*ops[i])(_pop);
++_pop;
}

1
eo/src/ga.h
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@ -34,6 +34,7 @@
// the operators
#include "ga/eoBitOp.h"
#include "ga/eoStandardBitMutation.h"
// #include <ga/eoBitOpFactory.h> to be corrected - thanks someone!

213
eo/src/ga/eoStandardBitMutation.h Normal file
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@ -0,0 +1,213 @@
#ifndef _eoStandardBitMutation_h_
#define _eoStandardBitMutation_h_
#include "../utils/eoRNG.h"
/** Standard bit mutation with mutation rate p:
* choose k from the binomial distribution Bin(n,p) and apply flip_k(x).
*
* @ingroup Bitstrings
* @ingroup Variators
*/
template<class EOT>
class eoStandardBitMutation : public eoMonOp<EOT>
{
public:
eoStandardBitMutation(double rate = 0.5) :
_rate(rate),
_nb(1),
_bitflip(_nb)
{}
virtual bool operator()(EOT& chrom)
{
_nb = eo::rng.binomial(chrom.size(),_rate);
// BitFlip operator is bound to the _nb reference,
// thus one don't need to re-instantiate.
return _bitflip(chrom);
}
protected:
double _rate;
unsigned _nb;
eoDetSingleBitFlip<EOT> _bitflip;
};
/** Uniform bit mutation with mutation rate p:
* choose k from the uniform distribution U(0,n) and apply flip_k(x).
*
* @ingroup Bitstrings
* @ingroup Variators
*/
template<class EOT>
class eoUniformBitMutation : public eoMonOp<EOT>
{
public:
eoUniformBitMutation(double rate = 0.5) :
_rate(rate),
_nb(1),
_bitflip(_nb)
{}
virtual bool operator()(EOT& chrom)
{
_nb = eo::rng.random(chrom.size());
// BitFlip operator is bound to the _nb reference,
// thus one don't need to re-instantiate.
return _bitflip(chrom);
}
protected:
double _rate;
unsigned _nb;
eoDetSingleBitFlip<EOT> _bitflip;
};
/** Conditional standard bit mutation with mutation rate p:
* choose k from the binomial distribution Bin(n,p) until k >0
* and apply flip_k(x).
*
* This is identical to sampling k from the conditional binomial
* distribution Bin>0(n,p) which re-assigns the probability to sample
* a 0 proportionally to all values i ∈ [1..n].
*
* @ingroup Bitstrings
* @ingroup Variators
*/
template<class EOT>
class eoConditionalBitMutation : public eoStandardBitMutation<EOT>
{
public:
eoConditionalBitMutation(double rate = 0.5) :
eoStandardBitMutation<EOT>(rate)
{}
virtual bool operator()(EOT& chrom)
{
assert(chrom.size()>0);
this->_nb = eo::rng.binomial(chrom.size()-1,this->_rate);
this->_nb++;
// BitFlip operator is bound to the _nb reference,
// thus one don't need to re-instantiate.
return this->_bitflip(chrom);
}
};
/** Shifted standard bit mutation with mutation rate p:
* choose k from the binomial distribution Bin(n,p).
* When k= 0, set k= 1. Apply flip_k(x).
*
* This is identical to sampling k from the conditional binomial
* distribution Bin0→1(n,p) which re-assigns the probability to
* sample a 0 to sampling k= 1.
*
* @ingroup Bitstrings
* @ingroup Variators
*/
template<class EOT>
class eoShiftedBitMutation : public eoStandardBitMutation<EOT>
{
public:
eoShiftedBitMutation(double rate = 0.5) :
eoStandardBitMutation<EOT>(rate)
{}
virtual bool operator()(EOT& chrom)
{
assert(chrom.size()>0);
this->_nb = eo::rng.binomial(chrom.size()-1,this->_rate);
if(this->_nb == 0) {
this->_nb = 1;
}
// BitFlip operator is bound to the _nb reference,
// thus one don't need to re-instantiate.
return this->_bitflip(chrom);
}
};
/** Mutation which size is sample in a gaussian.
*
* sample k from the normal distribution N(pn,σ^2)
* and apply flip_k(x).
*
* From:
* Furong Ye, Carola Doerr, and Thomas Back.
* Interpolating local and global search by controllingthe variance of standard bit mutation.
* In 2019 IEEE Congress on Evolutionary Computation(CEC), pages 2292–2299.
*
* In contrast to standard bit mutation, this operators allows to scale
* the variance of the mutation strength independently of the mean.
*
* @ingroup Bitstrings
* @ingroup Variators
*/
template<class EOT>
class eoNormalBitMutation : public eoStandardBitMutation<EOT>
{
public:
eoNormalBitMutation(double rate = 0.5, double variance = 1) :
eoStandardBitMutation<EOT>(rate),
_variance(variance)
{}
virtual bool operator()(EOT& chrom)
{
this->_nb = eo::rng.normal(this->_rate * chrom.size(), _variance);
if(this->_nb >= chrom.size()) {
this->_nb = eo::rng.random(chrom.size());
}
// BitFlip operator is bound to the _nb reference,
// thus one don't need to re-instantiate.
return this->_bitflip(chrom);
}
protected:
double _variance;
};
/** Fast mutation which size is sampled from an adaptive power law.
*
* From:
* Benjamin Doerr, Huu Phuoc Le, Régis Makhmara, and Ta Duy Nguyen.
* Fast genetic algorithms.
* In Proc. of Genetic and Evolutionary Computation Conference (GECCO’17), pages 777–784.ACM, 2017.
*
* @ingroup Bitstrings
* @ingroup Variators
*/
template<class EOT>
class eoFastBitMutation : public eoStandardBitMutation<EOT>
{
public:
eoFastBitMutation(double rate = 0.5, double beta = 1.5) :
eoStandardBitMutation<EOT>(rate),
_beta(beta)
{
assert(beta > 1);
}
virtual bool operator()(EOT& chrom)
{
this->_nb = powerlaw(chrom.size(),_beta);
// BitFlip operator is bound to the _nb reference,
// thus one don't need to re-instantiate.
return this->_bitflip(chrom);
}
protected:
double powerlaw(unsigned n, double beta)
{
double cnb = 0;
for(unsigned i=1; i<n; ++i) {
cnb += std::pow(i,-beta);
}
return eo::rng.powerlaw(0,n,beta) / cnb;
}
double _beta;
};
#endif // _eoStandardBitMutation_h_

14
eo/src/utils/eoRNG.h
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@ -216,7 +216,7 @@ public :
return uniform() < bias;
}
/** Sample in a binomial dsitribution of size n and probability p.
/** Sample in a binomial distribution of size n and probability p.
FIXME most naive algorithm, one should really use a rejection algorithm.
*/
@ -229,6 +229,18 @@ public :
return x;
}
/** Sample in a power law distribution
*/
double powerlaw(double min, double max, double gamma)
{
double x = uniform(min,max);
return std::pow(
x * (std::pow(max,-gamma+1) - std::pow(min,-gamma+1))
+ std::pow(min,-gamma+1.0),
1.0/(-gamma + 1.0)
);
}
/** Gaussian deviate
Zero mean Gaussian deviate with standard deviation 1.