/*! * * * \brief Convex benchmark function. * * * \author T. Voss * \date 2010-2011 * * * \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 . * */ #ifndef SHARK_OBJECTIVEFUNCTIONS_BENCHMARK_SCHWEFEL_H #define SHARK_OBJECTIVEFUNCTIONS_BENCHMARK_SCHWEFEL_H #include #include namespace shark { /** * \brief Convex benchmark function. */ struct Schwefel : public SingleObjectiveFunction { Schwefel(std::size_t numberOfVariables = 5):m_numberOfVariables(numberOfVariables) { m_features |= CAN_PROPOSE_STARTING_POINT; } /// \brief From INameable: return the class name. std::string name() const { return "Schwefel"; } std::size_t numberOfVariables()const{ return m_numberOfVariables; } bool hasScalableDimensionality()const{ return true; } void setNumberOfVariables( std::size_t numberOfVariables ){ m_numberOfVariables = numberOfVariables; } SearchPointType proposeStartingPoint() const { RealVector x(numberOfVariables()); for (std::size_t i = 0; i < x.size(); i++) { x(i) = random::gauss(*mep_rng, 0,1); } return x; } double eval(const SearchPointType &p) const { m_evaluationCounter++; double value = 0; double sum= 0; for(std::size_t i = 0; i != m_numberOfVariables; ++i){ sum+= p(i); value+=sqr(sum); } return value; } private: std::size_t m_numberOfVariables; }; } #endif