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Hadrons: a bit of cleaning in the scheduler
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51322da6f8
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4a87486365
@ -40,7 +40,9 @@ template <typename T>
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class GeneticScheduler
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{
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public:
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typedef std::function<int(const std::vector<T> &)> ObjFunc;
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typedef std::vector<T> Gene;
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typedef std::pair<Gene *, Gene *> GenePair;
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typedef std::function<int(const Gene &)> ObjFunc;
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struct Parameters
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{
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double mutationRate;
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@ -53,8 +55,8 @@ public:
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// destructor
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virtual ~GeneticScheduler(void) = default;
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// access
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const std::vector<T> & getMinSchedule(void);
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int getMinValue(void);
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const Gene & getMinSchedule(void);
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int getMinValue(void);
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// breed a new generation
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void nextGeneration(void);
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// print population
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@ -71,19 +73,20 @@ public:
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return out;
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}
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private:
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// randomly initialize population
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// evolution steps
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void initPopulation(void);
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void doCrossover(void);
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void doMutation(void);
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// genetic operators
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std::vector<T> * select1(void);
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std::pair<std::vector<T> *, std::vector<T> *> select2(void);
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void crossover(void);
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void mutation(void);
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GenePair selectPair(void);
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void crossover(Gene &c, const Gene &p1, const Gene &p2);
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void mutation(Gene &m, const Gene &c);
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private:
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Graph<T> &graph_;
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const ObjFunc &func_;
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const Parameters par_;
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std::multimap<int, std::vector<T>> population_;
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std::mt19937 gen_;
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Graph<T> &graph_;
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const ObjFunc &func_;
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const Parameters par_;
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std::multimap<int, Gene> population_;
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std::mt19937 gen_;
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};
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/******************************************************************************
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@ -102,7 +105,8 @@ GeneticScheduler<T>::GeneticScheduler(Graph<T> &graph, const ObjFunc &func,
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// access //////////////////////////////////////////////////////////////////////
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template <typename T>
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const std::vector<T> & GeneticScheduler<T>::getMinSchedule(void)
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const typename GeneticScheduler<T>::Gene &
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GeneticScheduler<T>::getMinSchedule(void)
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{
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return population_.begin()->second;
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}
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@ -128,7 +132,7 @@ void GeneticScheduler<T>::nextGeneration(void)
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PARALLEL_FOR_LOOP
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for (unsigned int i = 0; i < par_.popSize; ++i)
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{
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mutation();
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doMutation();
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}
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LOG(Debug) << "After mutations:\n" << *this << std::endl;
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@ -136,7 +140,7 @@ void GeneticScheduler<T>::nextGeneration(void)
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PARALLEL_FOR_LOOP
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for (unsigned int i = 0; i < par_.popSize/2; ++i)
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{
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crossover();
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doCrossover();
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}
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LOG(Debug) << "After mating:\n" << *this << std::endl;
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@ -148,7 +152,7 @@ void GeneticScheduler<T>::nextGeneration(void)
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LOG(Debug) << "After grim reaper:\n" << *this << std::endl;
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}
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// randomly initialize population //////////////////////////////////////////////
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// evolution steps /////////////////////////////////////////////////////////////
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template <typename T>
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void GeneticScheduler<T>::initPopulation(void)
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{
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@ -161,24 +165,50 @@ void GeneticScheduler<T>::initPopulation(void)
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}
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}
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// genetic operators ///////////////////////////////////////////////////////////
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template <typename T>
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std::vector<T> * GeneticScheduler<T>::select1(void)
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void GeneticScheduler<T>::doCrossover(void)
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{
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std::uniform_int_distribution<unsigned int> pdis(0, population_.size() - 1);
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auto p = selectPair();
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auto &p1 = *(p.first), &p2 = *(p.second);
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Gene c1, c2;
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auto it = population_.begin();
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std::advance(it, pdis(gen_));
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return &(it->second);
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crossover(c1, p1, p2);
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crossover(c2, p2, p1);
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PARALLEL_CRITICAL
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{
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population_.emplace(func_(c1), c1);
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population_.emplace(func_(c2), c2);
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}
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}
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template <typename T>
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std::pair<std::vector<T> *, std::vector<T> *> GeneticScheduler<T>::select2(void)
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void GeneticScheduler<T>::doMutation(void)
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{
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std::uniform_real_distribution<double> mdis(0., 1.);
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std::uniform_int_distribution<unsigned int> pdis(0, population_.size() - 1);
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if (mdis(gen_) < par_.mutationRate)
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{
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Gene m;
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auto it = population_.begin();
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std::advance(it, pdis(gen_));
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mutation(m, it->second);
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PARALLEL_CRITICAL
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{
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population_.erase(it);
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population_.emplace(func_(m), m);
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}
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}
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}
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// genetic operators ///////////////////////////////////////////////////////////
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template <typename T>
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typename GeneticScheduler<T>::GenePair GeneticScheduler<T>::selectPair(void)
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{
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std::vector<double> prob;
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unsigned int ind;
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std::vector<T> *p1, *p2;
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Gene *p1, *p2;
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for (auto &c: population_)
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{
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@ -206,76 +236,52 @@ std::pair<std::vector<T> *, std::vector<T> *> GeneticScheduler<T>::select2(void)
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}
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template <typename T>
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void GeneticScheduler<T>::crossover(void)
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void GeneticScheduler<T>::crossover(Gene &c, const Gene &p1, const Gene &p2)
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{
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auto p = select2();
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auto &p1 = *(p.first),
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&p2 = *(p.second);
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std::uniform_int_distribution<unsigned int> dis2(0, p1.size() - 1);
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unsigned int cut = dis2(gen_);
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std::vector<T> c1, c2, buf;
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Gene buf;
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std::uniform_int_distribution<unsigned int> dis(0, p1.size() - 1);
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unsigned int cut = dis(gen_);
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auto cross = [&buf, cut](std::vector<T> &c, const std::vector<T> &p1,
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const std::vector<T> &p2)
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c.clear();
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buf = p1;
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for (unsigned int i = 0; i < cut; ++i)
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{
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buf = p1;
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for (unsigned int i = 0; i < cut; ++i)
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{
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c.push_back(p2[i]);
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buf.erase(std::find(buf.begin(), buf.end(), p2[i]));
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}
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for (unsigned int i = 0; i < buf.size(); ++i)
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{
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c.push_back(buf[i]);
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}
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};
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cross(c1, p1, p2);
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cross(c2, p2, p1);
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PARALLEL_CRITICAL
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c.push_back(p2[i]);
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buf.erase(std::find(buf.begin(), buf.end(), p2[i]));
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}
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for (unsigned int i = 0; i < buf.size(); ++i)
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{
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population_.emplace(func_(c1), c1);
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population_.emplace(func_(c2), c2);
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c.push_back(buf[i]);
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}
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}
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template <typename T>
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void GeneticScheduler<T>::mutation(void)
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void GeneticScheduler<T>::mutation(Gene &m, const Gene &c)
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{
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std::uniform_real_distribution<double> mdis(0., 1.);
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Gene buf;
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std::uniform_int_distribution<unsigned int> dis(0, c.size() - 1);
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unsigned int cut = dis(gen_);
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Graph<T> g1 = graph_, g2 = graph_;
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if (mdis(gen_) < par_.mutationRate)
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for (unsigned int i = 0; i < cut; ++i)
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{
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auto &c = *select1();
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std::uniform_int_distribution<unsigned int> cdis(0, c.size() - 1);
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unsigned int cut = cdis(gen_);
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std::vector<T> buf1, buf2;
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Graph<T> g1 = graph_, g2 = graph_;
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for (unsigned int i = 0; i < cut; ++i)
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{
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g1.removeVertex(c[i]);
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}
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for (unsigned int i = cut; i < c.size(); ++i)
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{
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g2.removeVertex(c[i]);
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}
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if (g1.size() > 0)
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{
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buf1 = g1.topoSort(gen_);
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}
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if (g2.size() > 0)
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{
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buf2 = g2.topoSort(gen_);
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}
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for (unsigned int i = cut; i < c.size(); ++i)
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{
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buf2.push_back(buf1[i - cut]);
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}
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PARALLEL_CRITICAL
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{
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population_.emplace(func_(buf2), buf2);
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}
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g1.removeVertex(c[i]);
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}
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for (unsigned int i = cut; i < c.size(); ++i)
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{
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g2.removeVertex(c[i]);
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}
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if (g1.size() > 0)
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{
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buf = g1.topoSort(gen_);
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}
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if (g2.size() > 0)
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{
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m = g2.topoSort(gen_);
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}
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for (unsigned int i = cut; i < c.size(); ++i)
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{
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m.push_back(buf[i - cut]);
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}
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}
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