/*!
*
*
* \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