mirror of
https://github.com/paboyle/Grid.git
synced 2024-11-10 07:55:35 +00:00
237 lines
7.0 KiB
C++
237 lines
7.0 KiB
C++
/*******************************************************************************
|
|
Grid physics library, www.github.com/paboyle/Grid
|
|
|
|
Source file: programs/Hadrons/GeneticScheduler.hpp
|
|
|
|
Copyright (C) 2016
|
|
|
|
Author: Antonin Portelli <antonin.portelli@me.com>
|
|
|
|
This program is free software; you can redistribute it and/or modify
|
|
it under the terms of the GNU General Public License as published by
|
|
the Free Software Foundation; either version 2 of the License, or
|
|
(at your option) any later version.
|
|
|
|
This program is distributed in the hope that it will be useful,
|
|
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
|
GNU General Public License for more details.
|
|
|
|
You should have received a copy of the GNU General Public License along
|
|
with this program; if not, write to the Free Software Foundation, Inc.,
|
|
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
|
|
|
|
See the full license in the file "LICENSE" in the top level distribution
|
|
directory.
|
|
*******************************************************************************/
|
|
|
|
#ifndef Hadrons_GeneticScheduler_hpp_
|
|
#define Hadrons_GeneticScheduler_hpp_
|
|
|
|
#include <Hadrons/Global.hpp>
|
|
#include <Hadrons/Graph.hpp>
|
|
|
|
BEGIN_HADRONS_NAMESPACE
|
|
|
|
/******************************************************************************
|
|
* Scheduler based on a genetic algorithm *
|
|
******************************************************************************/
|
|
template <typename T>
|
|
class GeneticScheduler
|
|
{
|
|
public:
|
|
typedef std::function<int(const std::vector<T> &)> ObjFunc;
|
|
struct Parameters
|
|
{
|
|
double mutationRate;
|
|
unsigned int popSize, seed;
|
|
};
|
|
public:
|
|
// constructor
|
|
GeneticScheduler(Graph<T> &graph, const ObjFunc &func,
|
|
const Parameters &par);
|
|
// destructor
|
|
virtual ~GeneticScheduler(void) = default;
|
|
// access
|
|
const std::vector<T> & getMinSchedule(void);
|
|
int getMinValue(void);
|
|
// breed a new generation
|
|
void nextGeneration(void);
|
|
// print population
|
|
friend std::ostream & operator<<(std::ostream &out,
|
|
const GeneticScheduler<T> &s)
|
|
{
|
|
for (auto &p: s.population_)
|
|
{
|
|
out << p.second << ": " << p.first << std::endl;
|
|
}
|
|
|
|
return out;
|
|
}
|
|
private:
|
|
// randomly initialize population
|
|
void initPopulation(void);
|
|
// genetic operators
|
|
const std::vector<T> & selection(void);
|
|
void crossover(const std::vector<T> &c1,
|
|
const std::vector<T> &c2);
|
|
void mutation(std::vector<T> &c);
|
|
private:
|
|
Graph<T> &graph_;
|
|
const ObjFunc &func_;
|
|
const Parameters par_;
|
|
std::multimap<int, std::vector<T>> population_;
|
|
std::mt19937 gen_;
|
|
};
|
|
|
|
/******************************************************************************
|
|
* template implementation *
|
|
******************************************************************************/
|
|
// constructor /////////////////////////////////////////////////////////////////
|
|
template <typename T>
|
|
GeneticScheduler<T>::GeneticScheduler(Graph<T> &graph, const ObjFunc &func,
|
|
const Parameters &par)
|
|
: graph_(graph)
|
|
, func_(func)
|
|
, par_(par)
|
|
{
|
|
gen_.seed(par_.seed);
|
|
}
|
|
|
|
// access //////////////////////////////////////////////////////////////////////
|
|
template <typename T>
|
|
const std::vector<T> & GeneticScheduler<T>::getMinSchedule(void)
|
|
{
|
|
return population_.begin()->second;
|
|
}
|
|
|
|
template <typename T>
|
|
int GeneticScheduler<T>::getMinValue(void)
|
|
{
|
|
return population_.begin()->first;
|
|
}
|
|
|
|
// breed a new generation //////////////////////////////////////////////////////
|
|
template <typename T>
|
|
void GeneticScheduler<T>::nextGeneration(void)
|
|
{
|
|
std::uniform_real_distribution<double> dis(0., 1.);
|
|
|
|
// random initialization of the population if necessary
|
|
if (population_.size() != par_.popSize)
|
|
{
|
|
initPopulation();
|
|
}
|
|
|
|
// mating
|
|
for (unsigned int i = 0; i < par_.popSize/2; ++i)
|
|
{
|
|
auto &p1 = selection(), &p2 = selection();
|
|
crossover(p1, p2);
|
|
}
|
|
|
|
// random mutations
|
|
auto buf = population_;
|
|
population_.clear();
|
|
for (auto &c: buf)
|
|
{
|
|
if (dis(gen_) < par_.mutationRate)
|
|
{
|
|
mutation(c.second);
|
|
}
|
|
population_.emplace(func_(c.second), c.second);
|
|
}
|
|
|
|
// grim reaper
|
|
auto it = population_.begin();
|
|
|
|
std::advance(it, par_.popSize);
|
|
population_.erase(it, population_.end());
|
|
}
|
|
|
|
// randomly initialize population //////////////////////////////////////////////
|
|
template <typename T>
|
|
void GeneticScheduler<T>::initPopulation(void)
|
|
{
|
|
population_.clear();
|
|
for (unsigned int i = 0; i < par_.popSize; ++i)
|
|
{
|
|
auto p = graph_.topoSort(gen_);
|
|
|
|
population_.emplace(func_(p), p);
|
|
}
|
|
}
|
|
|
|
// genetic operators ///////////////////////////////////////////////////////////
|
|
template <typename T>
|
|
const std::vector<T> & GeneticScheduler<T>::selection(void)
|
|
{
|
|
std::vector<double> prob;
|
|
|
|
for (auto &c: population_)
|
|
{
|
|
prob.push_back(1./c.first);
|
|
}
|
|
std::discrete_distribution<unsigned int> dis(prob.begin(), prob.end());
|
|
auto rIt = population_.begin();
|
|
std::advance(rIt, dis(gen_));
|
|
|
|
return rIt->second;
|
|
}
|
|
|
|
template <typename T>
|
|
void GeneticScheduler<T>::crossover(const std::vector<T> &p1,
|
|
const std::vector<T> &p2)
|
|
{
|
|
std::uniform_int_distribution<unsigned int> dis(0, p1.size() - 1);
|
|
unsigned int cut = dis(gen_);
|
|
std::vector<T> c1, c2, buf;
|
|
|
|
auto cross = [&buf, cut](std::vector<T> &c, const std::vector<T> &p1,
|
|
const std::vector<T> &p2)
|
|
{
|
|
buf = p2;
|
|
for (unsigned int i = 0; i < cut; ++i)
|
|
{
|
|
c.push_back(p1[i]);
|
|
buf.erase(std::find(buf.begin(), buf.end(), p1[i]));
|
|
}
|
|
for (unsigned int i = 0; i < buf.size(); ++i)
|
|
{
|
|
c.push_back(buf[i]);
|
|
}
|
|
};
|
|
|
|
cross(c1, p1, p2);
|
|
cross(c2, p2, p1);
|
|
population_.emplace(func_(c1), c1);
|
|
population_.emplace(func_(c2), c2);
|
|
}
|
|
|
|
template <typename T>
|
|
void GeneticScheduler<T>::mutation(std::vector<T> &c)
|
|
{
|
|
std::uniform_int_distribution<unsigned int> dis(0, c.size() - 1);
|
|
unsigned int cut = dis(gen_);
|
|
Graph<T> g = graph_;
|
|
std::vector<T> buf;
|
|
|
|
for (unsigned int i = cut; i < c.size(); ++i)
|
|
{
|
|
g.removeVertex(c[i]);
|
|
}
|
|
if (g.size() > 0)
|
|
{
|
|
buf = g.topoSort(gen_);
|
|
}
|
|
for (unsigned int i = cut; i < c.size(); ++i)
|
|
{
|
|
buf.push_back(c[i]);
|
|
}
|
|
c = buf;
|
|
}
|
|
|
|
END_HADRONS_NAMESPACE
|
|
|
|
#endif // Hadrons_GeneticScheduler_hpp_
|