luksan_vlcek_3.cpp

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#include <boost/integer_traits.hpp>
#include <cmath>
#include <stdexcept>
#include <string>
#include <vector>

#include "../exceptions.h"
#include "../types.h"
#include "base.h"
#include "luksan_vlcek_3.h"

static int __check__(int N){
        if (N < 8 || (N) % 4)
        {
                pagmo_throw(value_error,"problem dimension N needs to be at least 8 and a multiple of 4");
        }
        return N;
}

namespace pagmo { namespace problem {


luksan_vlcek_3::luksan_vlcek_3(int N, const double &clb, const double &cub):base(__check__(N), 0, 1, 2 * 2, 2 * 2, 1e-14)
{
        if (clb > cub)
        {
                pagmo_throw(value_error,"constraints lower bound is higher than the upper bound");
        }
        set_lb(-5);
        set_ub(5);
        m_clb = std::vector<double>(2,clb);
        m_cub = std::vector<double>(2,cub);
}

base_ptr luksan_vlcek_3::clone() const
{
        return base_ptr(new luksan_vlcek_3(*this));
}

void luksan_vlcek_3::objfun_impl(fitness_vector &f, const decision_vector &x) const
{
        f[0] = 0.;
        for (decision_vector::size_type i=0; i<(x.size()-2)/2; i++)
        {
                double a1 = x[2*i]+10.*x[2*i+1];
                double a2 = x[2*i+2] - x[2*i+3];
                double a3 = x[2*i+1] - 2.*x[2*i+2];
                double a4 = x[2*i] - x[2*i+3];
                f[0] += a1*a1 + 5.*a2*a2 + std::pow(a3,4)+ 10.*std::pow(a4,4);
        }

}
void luksan_vlcek_3::compute_constraints_impl(constraint_vector &c, const decision_vector &x) const
{
        int n = x.size();
        c[0] = 3.*std::pow(x[0],3) + 2.*x[1] - 5. + std::sin(x[0]-x[1])*std::sin(x[0]+x[1]) - m_cub[0];
        c[1] = m_clb[0] - ( 3.*std::pow(x[0],3) + 2.*x[1] - 5. + std::sin(x[0]-x[1])*std::sin(x[0]+x[1]) );
        c[2] = 4.*x[n-3] - x[n-4]*std::exp(x[n-4]-x[n-3]) - 3 - m_cub[1];
        c[3] = m_clb[1] - ( 4.*x[n-3] - x[n-4]*std::exp(x[n-4]-x[n-3]) - 3 );
}

void luksan_vlcek_3::set_sparsity(int &lenG, std::vector<int> &iGfun, std::vector<int> &jGvar) const
{
        //Initial point
        decision_vector x0(get_dimension(),1);
        //Numerical procedure
        estimate_sparsity(x0, lenG, iGfun, jGvar);
}

std::string luksan_vlcek_3::get_name() const
{
        return "Luksan-Vlcek 3";
}

}}

BOOST_CLASS_EXPORT_IMPLEMENT(pagmo::problem::luksan_vlcek_3)