//=========================================================================== /*! * * * \brief Multi-objective optimization benchmark function LZ2. * * The function is described in * * H. Li and Q. Zhang. * Multiobjective Optimization Problems with Complicated Pareto Sets, MOEA/D and NSGA-II, * IEEE Trans on Evolutionary Computation, 2(12):284-302, April 2009. * * * * \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_LZ2_H #define SHARK_OBJECTIVEFUNCTIONS_BENCHMARK_LZ2_H #include #include namespace shark { /*! \brief Multi-objective optimization benchmark function LZ2. * * The function is described in * * H. Li and Q. Zhang. * Multiobjective Optimization Problems with Complicated Pareto Sets, MOEA/D and NSGA-II, * IEEE Trans on Evolutionary Computation, 2(12):284-302, April 2009. */ struct LZ2 : public MultiObjectiveFunction { LZ2(std::size_t numVariables = 0) : m_handler(SearchPointType(numVariables,-1),SearchPointType(numVariables,1) ){ announceConstraintHandler(&m_handler); } /// \brief From INameable: return the class name. std::string name() const { return "LZ2"; } std::size_t numberOfObjectives()const{ return 2; } 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 ){ SearchPointType lb(numberOfVariables,-1); SearchPointType ub(numberOfVariables, 1); lb(0) = 0; ub(0) = 1; m_handler.setBounds(lb, ub); } ResultType eval( const SearchPointType & x ) const { m_evaluationCounter++; ResultType value( 2, 0 ); std::size_t counter1 = 0, counter2 = 0; for( std::size_t i = 1; i < x.size(); i++ ) { if( i % 2 == 0 ) { counter2++; value[1] += sqr( x(i) - ::sin( 6 * M_PI * x( 0 ) + i*M_PI/x.size() ) ); } else { counter1++; value[0] += sqr( x(i) - ::sin( 6 * M_PI * x( 0 ) + i*M_PI/x.size() ) ); } } value[0] *= 2./counter1; value[0] += x( 0 ); value[1] *= 2./counter2; value[1] += 1 - ::sqrt( x( 0 ) ); return value; } private: BoxConstraintHandler m_handler; }; } #endif