//=========================================================================== /*! * * * \brief Multi-objective optimization benchmark function ZDT3 * * The function is described in * * Eckart Zitzler, Kalyanmoy Deb, and Lothar Thiele. Comparison of * Multiobjective Evolutionary Algorithms: Empirical * Results. Evolutionary Computation 8(2):173-195, 2000 * * * * \author - * \date - * * * \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 . * */ //=========================================================================== #ifndef SHARK_OBJECTIVEFUNCTIONS_BENCHMARK_ZDT3_H #define SHARK_OBJECTIVEFUNCTIONS_BENCHMARK_ZDT3_H #include #include namespace shark { /*! \brief Multi-objective optimization benchmark function ZDT3 * * The function is described in * * Eckart Zitzler, Kalyanmoy Deb, and Lothar Thiele. Comparison of * Multiobjective Evolutionary Algorithms: Empirical * Results. Evolutionary Computation 8(2):173-195, 2000 */ struct ZDT3 : public MultiObjectiveFunction { ZDT3(std::size_t numVariables = 0) : m_handler(numVariables,0,1){ announceConstraintHandler(&m_handler); } /// \brief From INameable: return the class name. std::string name() const { return "ZDT3"; } std::size_t numberOfVariables()const{ return m_handler.dimensions(); } bool hasScalableDimensionality()const{ return true; } /// \brief Adjusts the number of variables if the function is scalable. /// \param [in] numberOfVariables The new dimension. void setNumberOfVariables( std::size_t numberOfVariables ){ m_handler.setBounds(numberOfVariables,0,1); } std::size_t numberOfObjectives()const{ return 2; } ResultType eval( const SearchPointType & x ) const { m_evaluationCounter++; ResultType value( 2 ); value[0] = x( 0 ); double g = 1.0 + 9.0 *(sum(x)-x(0))/(numberOfVariables() - 1.0); double h = 1.0 - std::sqrt(x(0) / g) - (x(0) / g) * std::sin(10 * M_PI * x(0)); value[1] = g * h; return value; } private: BoxConstraintHandler m_handler; }; } #endif