/usr/include/openturns/EfficientGlobalOptimization.hxx is in libopenturns-dev 1.9-5.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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/**
* @brief EfficientGlobalOptimization or EGO algorithm
*
* Copyright 2005-2017 Airbus-EDF-IMACS-Phimeca
*
* This library 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.
*
* This library 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
* along with this library. If not, see <http://www.gnu.org/licenses/>.
*
*/
#ifndef OPENTURNS_EFFICIENTGLOBALOPTIMIZATION_HXX
#define OPENTURNS_EFFICIENTGLOBALOPTIMIZATION_HXX
#include "openturns/OptimizationAlgorithmImplementation.hxx"
#include "openturns/OptimizationAlgorithm.hxx"
#include "openturns/KrigingResult.hxx"
BEGIN_NAMESPACE_OPENTURNS
/**
* @class EfficientGlobalOptimization
*/
class OT_API EfficientGlobalOptimization
: public OptimizationAlgorithmImplementation
{
CLASSNAME;
public:
/** Default constructor */
EfficientGlobalOptimization();
/** Constructor with parameters */
EfficientGlobalOptimization(const OptimizationProblem & problem,
const KrigingResult & krigingResult);
/** Virtual constructor */
virtual EfficientGlobalOptimization * clone() const;
/** String converter */
String __repr__() const;
/** Performs the actual computation. */
void run();
void setOptimizationAlgorithm(const OptimizationAlgorithm & solver);
OptimizationAlgorithm getOptimizationAlgorithm() const;
/** Size of the design to draw starting points */
UnsignedInteger getMultiStartExperimentSize() const;
void setMultiStartExperimentSize(const UnsignedInteger multiStartExperimentSize);
/** Number of starting points for the criterion optim */
UnsignedInteger getMultiStartNumber() const;
void setMultiStartNumber(const UnsignedInteger multiStartNumberSize);
/** Parameter estimation period accessor */
UnsignedInteger getParameterEstimationPeriod() const;
void setParameterEstimationPeriod(const UnsignedInteger parameterEstimationPeriod);
/** improvement stopping criterion factor accessor */
void setImprovementFactor(const Scalar improvementFactor);
Scalar getImprovementFactor() const;
/** correlation length stopping criterion factor accessor */
void setCorrelationLengthFactor(const Scalar b);
Scalar getCorrelationLengthFactor() const;
/** AEI tradeoff constant accessor */
void setAIETradeoff(const Scalar c);
Scalar getAIETradeoff() const;
/** Improvement noise function accessor */
void setNoiseModel(const Function & noiseModel);
Function getNoiseModel() const;
/** Expected improvement function */
Sample getExpectedImprovement() const;
/** Method save() stores the object through the StorageManager */
void save(Advocate & adv) const;
/** Method load() reloads the object from the StorageManager */
void load(Advocate & adv);
protected:
friend class Factory<EfficientGlobalOptimization>;
/** Check whether this problem can be solved by this solver. */
void checkProblem(const OptimizationProblem & problem) const;
private:
KrigingResult krigingResult_;
OptimizationAlgorithm solver_;
// whether the solver was set
mutable Bool useDefaultSolver_;
// Size of the design to draw starting points
UnsignedInteger multiStartExperimentSize_;
// number of starting points for criterion optim
UnsignedInteger multiStartNumber_;
// relearn kriging parameters every X iterations
UnsignedInteger parameterEstimationPeriod_;
// improvement stopping criterion factor
Scalar improvementFactor_;
// correlation length stopping criterion factor
Scalar correlationLengthFactor_;
// AEI tradeoff constant u(x)=mk(x)+c*sk(x)
Scalar aeiTradeoff_;
// optional noise model for improvement optimization only
// for the metamodel noise the 2nd marginal of the objective is used
Function noiseModel_;
mutable Sample expectedImprovement_;
} ; /* class EfficientGlobalOptimization */
END_NAMESPACE_OPENTURNS
#endif /* OPENTURNS_EFFICIENTGLOBALOPTIMIZATION_HXX */
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