office-gobmx/sccomp/source/solver/ParticelSwarmOptimization.hxx
Noel Grandin 1ab27f9ae6 loplugin:constfields in scaddins,sccomp
Change-Id: I4d21cfcc65c099fbddbe5146fc1b8a6257971e32
Reviewed-on: https://gerrit.libreoffice.org/61555
Tested-by: Jenkins
Reviewed-by: Noel Grandin <noel.grandin@collabora.co.uk>
2018-10-09 08:11:05 +02:00

179 lines
5.6 KiB
C++

/* -*- Mode: C++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
* This file is part of the LibreOffice project.
*
* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/.
*
*/
#ifndef INCLUDED_SCCOMP_SOURCE_PARTICLESWARM_HXX
#define INCLUDED_SCCOMP_SOURCE_PARTICLESWARM_HXX
#include <vector>
#include <random>
#include <limits>
struct Particle
{
Particle(size_t nDimensionality)
: mVelocity(nDimensionality)
, mPosition(nDimensionality)
, mCurrentFitness(std::numeric_limits<float>::lowest())
, mBestPosition(nDimensionality)
, mBestFitness(std::numeric_limits<float>::lowest())
{
}
std::vector<double> mVelocity;
std::vector<double> mPosition;
double mCurrentFitness;
std::vector<double> mBestPosition;
double mBestFitness;
};
template <typename DataProvider> class ParticleSwarmOptimizationAlgorithm
{
private:
// inertia
static constexpr double constWeight = 0.729;
// cognitive coefficient
static constexpr double c1 = 1.49445;
// social coefficient
static constexpr double c2 = 1.49445;
static constexpr double constAcceptedPrecision = 0.000000001;
DataProvider& mrDataProvider;
size_t const mnNumOfParticles;
std::vector<Particle> maSwarm;
std::random_device maRandomDevice;
std::mt19937 maGenerator;
size_t mnDimensionality;
std::uniform_real_distribution<> maRandom01;
std::vector<double> maBestPosition;
double mfBestFitness;
int mnGeneration;
int mnLastChange;
public:
ParticleSwarmOptimizationAlgorithm(DataProvider& rDataProvider, size_t nNumOfParticles)
: mrDataProvider(rDataProvider)
, mnNumOfParticles(nNumOfParticles)
, maGenerator(maRandomDevice())
, mnDimensionality(mrDataProvider.getDimensionality())
, maRandom01(0.0, 1.0)
, maBestPosition(mnDimensionality)
, mfBestFitness(std::numeric_limits<float>::lowest())
, mnGeneration(0)
, mnLastChange(0)
{
}
std::vector<double> const& getResult() { return maBestPosition; }
int getGeneration() { return mnGeneration; }
int getLastChange() { return mnLastChange; }
void initialize()
{
mnGeneration = 0;
mnLastChange = 0;
maSwarm.clear();
mfBestFitness = std::numeric_limits<float>::lowest();
maSwarm.reserve(mnNumOfParticles);
for (size_t i = 0; i < mnNumOfParticles; i++)
{
maSwarm.emplace_back(mnDimensionality);
Particle& rParticle = maSwarm.back();
mrDataProvider.initializeVariables(rParticle.mPosition, maGenerator);
mrDataProvider.initializeVariables(rParticle.mVelocity, maGenerator);
for (size_t k = 0; k < mnDimensionality; k++)
{
rParticle.mPosition[k] = mrDataProvider.clampVariable(k, rParticle.mPosition[k]);
}
rParticle.mCurrentFitness = mrDataProvider.calculateFitness(rParticle.mPosition);
for (size_t k = 0; k < mnDimensionality; k++)
{
rParticle.mPosition[k] = mrDataProvider.clampVariable(k, rParticle.mPosition[k]);
}
std::copy(rParticle.mPosition.begin(), rParticle.mPosition.end(),
rParticle.mBestPosition.begin());
rParticle.mBestFitness = rParticle.mCurrentFitness;
if (rParticle.mCurrentFitness > mfBestFitness)
{
mfBestFitness = rParticle.mCurrentFitness;
std::copy(rParticle.mPosition.begin(), rParticle.mPosition.end(),
maBestPosition.begin());
}
}
}
bool next()
{
bool bBestChanged = false;
for (Particle& rParticle : maSwarm)
{
double fRandom1 = maRandom01(maGenerator);
double fRandom2 = maRandom01(maGenerator);
for (size_t k = 0; k < mnDimensionality; k++)
{
rParticle.mVelocity[k]
= (constWeight * rParticle.mVelocity[k])
+ (c1 * fRandom1 * (rParticle.mBestPosition[k] - rParticle.mPosition[k]))
+ (c2 * fRandom2 * (maBestPosition[k] - rParticle.mPosition[k]));
mrDataProvider.clampVariable(k, rParticle.mVelocity[k]);
rParticle.mPosition[k] += rParticle.mVelocity[k];
rParticle.mPosition[k] = mrDataProvider.clampVariable(k, rParticle.mPosition[k]);
}
rParticle.mCurrentFitness = mrDataProvider.calculateFitness(rParticle.mPosition);
if (rParticle.mCurrentFitness > rParticle.mBestFitness)
{
rParticle.mBestFitness = rParticle.mCurrentFitness;
std::copy(rParticle.mPosition.begin(), rParticle.mPosition.end(),
rParticle.mBestPosition.begin());
}
if (rParticle.mCurrentFitness > mfBestFitness)
{
if (std::abs(rParticle.mCurrentFitness - mfBestFitness) > constAcceptedPrecision)
{
bBestChanged = true;
mnLastChange = mnGeneration;
}
std::copy(rParticle.mPosition.begin(), rParticle.mPosition.end(),
maBestPosition.begin());
mfBestFitness = rParticle.mCurrentFitness;
}
}
mnGeneration++;
return bBestChanged;
}
};
#endif
/* vim:set shiftwidth=4 softtabstop=4 expandtab: */