sga_gray.h

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 *   Copyright (C) 2004-2015 The PaGMO development team,                     *
 *   Advanced Concepts Team (ACT), European Space Agency (ESA)               *
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#ifndef PAGMO_ALGORITHM_SGA_GRAY_H
#define PAGMO_ALGORITHM_SGA_GRAY_H

#include "../config.h"
#include "../problem/base.h"
#include "../serialization.h"
#include "base.h"

namespace pagmo { namespace algorithm {


class __PAGMO_VISIBLE sga_gray: public base
{
public:
        struct selection {
                enum type {BEST20 = 0,ROULETTE = 1};
        };
        struct mutation {
                enum type {UNIFORM = 0};
        };

        struct crossover {
                enum type {SINGLE_POINT = 0};
        };
        sga_gray(int gen  = 1, const double &cr = .95, const double &m = .02, int elitism = 1,
                         mutation::type mut  = mutation::UNIFORM,
                         selection::type sel = selection::ROULETTE,
                         crossover::type cro = crossover::SINGLE_POINT);
        base_ptr clone() const;
        void evolve(population &) const;
        std::string get_name() const;
protected:
        std::string human_readable_extra() const;
private:
        friend class boost::serialization::access;
        template <class Archive>
        void serialize(Archive &ar, const unsigned int)
        {
                ar & boost::serialization::base_object<base>(*this);
                ar & const_cast<int &>(m_gen);
                ar & const_cast<double &>(m_cr);
                ar & const_cast<double &>(m_m);
                ar & const_cast<int &>(m_elitism);
                ar & const_cast<mutation::type &>(m_mut);
                ar & const_cast<selection::type &>(m_sel);
                ar & const_cast<crossover::type &>(m_cro);
                ar & m_max_encoding_integer;
                ar & m_bit_encoding;
        }
        //Number of generations
        const int m_gen;
        //Crossover rate
        const double m_cr;
        //Mutation rate
        const double m_m;

        //Elitism (number of generations after which to reinsert the best)
        const int m_elitism;
        //Mutation
        const mutation::type m_mut;
        //Selection_type
        const selection::type m_sel;
        //Crossover_type
        const crossover::type m_cro;

private:
        // genetic algoritms operators
        std::vector<int> selection(const std::vector<fitness_vector> &, const problem::base &) const;
        void crossover(std::vector< std::vector<int> > &pop_x) const;
        void mutate(std::vector< std::vector<int> > &pop_x) const;

private:
        // binary conversion
        std::vector<int> double_to_binary(const double &number, const double &lb, const double &ub) const;
        double binary_to_double(const std::vector<int> &binary, const double &lb, const double &ub) const;
        std::vector<int> gray_to_binary(const std::vector<int> &gray) const;
        std::vector<int> binary_to_gray(const std::vector<int> &binary) const;

        // encoding/decoding
        std::vector<int> encode(const decision_vector &x_vector, const decision_vector &lb, const decision_vector &ub) const;
        decision_vector decode(const std::vector<int> &chrom, const decision_vector &lb, const decision_vector &ub) const;

        // encoding size
        int m_max_encoding_integer;
        int m_bit_encoding;
};

}} //namespaces

BOOST_CLASS_EXPORT_KEY(pagmo::algorithm::sga_gray)

#endif // PAGMO_ALGORITHM_SGA_GRAY_H