gafactory.h

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/*
    
  This file is a part of MOGAL, a Multi-Objective Genetic Algorithm
  Library.
  
  Copyright (C) 2008-2012 Jori Liesenborgs

  Contact: jori.liesenborgs@gmail.com

  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; either
  version 2.1 of the License, or (at your option) any later version.

  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., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  
  USA

*/

#ifndef MOGAL_GAFACTORY_H

#define MOGAL_GAFACTORY_H

#include "mogalconfig.h"
#include "geneticalgorithm.h"
#include "randomnumbergenerator.h"
#include <vector>

namespace mogal
{

class MOGAL_IMPORTEXPORT GAFactoryParams : public errut::ErrorBase
{
protected:
        GAFactoryParams()                                                                               { }
public:
        ~GAFactoryParams()                                                                              { }

        virtual bool write(serut::SerializationInterface &si) const = 0;

        virtual bool read(serut::SerializationInterface &si) = 0;
};

class MOGAL_IMPORTEXPORT GAFactory : public errut::ErrorBase
{
protected:
        GAFactory()                                                                                     { }
public:
        ~GAFactory()                                                                                    { }

        virtual GAFactoryParams *createParamsInstance() const = 0;
        
        virtual const GAFactoryParams *getCurrentParameters() const = 0;

        virtual bool init(const GAFactoryParams *pFactoryParams) = 0;

        virtual size_t getNumberOfFitnessComponents() const = 0;
        
        virtual Genome *createNewGenome() const = 0;

        virtual size_t getMaximalGenomeSize() const = 0;

        virtual size_t getMaximalFitnessSize() const = 0;

        virtual bool writeGenome(serut::SerializationInterface &si, const Genome *pGenome) const = 0;

        virtual bool writeGenomeFitness(serut::SerializationInterface &si, const Genome *pGenome) const = 0;

        virtual bool writeCommonGenerationInfo(serut::SerializationInterface &si) const = 0;

        virtual bool readGenome(serut::SerializationInterface &si, Genome **pGenome) const = 0;

        virtual bool readGenomeFitness(serut::SerializationInterface &si, Genome *pGenome) const = 0;

        virtual bool readCommonGenerationInfo(serut::SerializationInterface &si) = 0;

        virtual void onGeneticAlgorithmStep(int generation, bool *pGenerationInfoChanged, bool *pStopAlgorithm) = 0;

        virtual void onGeneticAlgorithmStart()                                                          { }

        virtual void onGeneticAlgorithmStop()                                                           { }

        virtual void onSortedPopulation(const std::vector<GenomeWrapper> &population)                   { }

        virtual void sort(std::vector<GenomeWrapper> &population) = 0;

        virtual void updateBestGenomes(std::vector<GenomeWrapper> &population) = 0;

        virtual void breed(const std::vector<GenomeWrapper> &population, 
                           std::vector<GenomeWrapper> &newPopulation) = 0;

        virtual void introduceMutations(std::vector<GenomeWrapper> &population) = 0;

        virtual Genome *selectPreferredGenome(const std::list<Genome *> &bestGenomes) const = 0;

        // TODO: for CUDA ND sort, see also copyFitnessValuesTo in genome.h
        virtual bool hasFloatingPointFitnessValues() const                                              { return false; }

        virtual const RandomNumberGenerator *getRandomNumberGenerator() const = 0;
protected:
        GeneticAlgorithm *getCurrentAlgorithm()                                                         { return m_pCurrentAlgorithm; }

        GeneticAlgorithmParams getCurrentAlgorithmParameters() const                                    { return m_gaParams; }
private:
        void setCurrentAlgorithm(GeneticAlgorithm *pAlgorithm, const GeneticAlgorithmParams &params)    { m_pCurrentAlgorithm = pAlgorithm; m_gaParams = params; }
        
        GeneticAlgorithm *m_pCurrentAlgorithm;
        GeneticAlgorithmParams m_gaParams;

        friend class GeneticAlgorithm;
};

} // end namespace

#endif // MOGAL_GAFACTORY_H