#ifndef SHARK_OBJECTIVEFUNCTIONS_BENCHMARK_FONSECA_H
#define SHARK_OBJECTIVEFUNCTIONS_BENCHMARK_FONSECA_H
//===========================================================================
/*!
*
*
* \brief Bi-objective real-valued benchmark function proposed by Fonseca and Flemming.
*
*
*
* \author -
* \date 2011
*
*
* \par Copyright 1995-2017 Shark Development Team
*
*
* This file is part of Shark.
*
*
* Shark 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 3 of the License, or
* (at your option) any later version.
*
* Shark 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 Shark. If not, see .
*
*/
//===========================================================================
#include
#include
#include
namespace shark {
/// \brief Bi-objective real-valued benchmark function proposed by Fonseca and Flemming.
///
/// Fonseca, C. M. and P. J. Fleming (1998). Multiobjective
/// optimization and multiple constraint handling with evolutionary
/// algorithms-Part II: Application example. IEEE Transactions on
/// Systems, Man, and Cybernetics, Part A: Systems and Humans 28(1),
/// 38-47
///
/// The default search space dimension is 3, but the function can
/// handle more dimensions.
struct Fonseca : public MultiObjectiveFunction {
Fonseca(std::size_t numVariables)
:m_handler(SearchPointType(numVariables,-4),SearchPointType(numVariables,4) ){
announceConstraintHandler(&m_handler);
}
/// \brief From INameable: return the class name.
std::string name() const
{ return "Fonseca"; }
std::size_t numberOfObjectives()const{
return 2;
}
std::size_t numberOfVariables()const{
return m_handler.dimensions();
}
bool hasScalableDimensionality()const{
return true;
}
void setNumberOfVariables( std::size_t numberOfVariables ){
m_handler.setBounds(
SearchPointType(numberOfVariables,-4),
SearchPointType(numberOfVariables,4)
);
}
ResultType eval( const SearchPointType & x ) const {
m_evaluationCounter++;
ResultType value( 2 );
const double d = 1. / std::sqrt( static_cast( x.size() ) );
double sum1 = 0., sum2 = 0.;
for( std::size_t i = 0; i < x.size(); i++ ) {
sum1 += sqr( x( i ) - d );
sum2 += sqr( x( i ) + d );
}
value[0] = 1-std::exp( - sum1 );
value[1] = 1-std::exp( - sum2 );
return value;
}
private:
BoxConstraintHandler m_handler;
};
}
#endif