#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