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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 16:51:28 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 16:51:28 +0000 |
commit | 940b4d1848e8c70ab7642901a68594e8016caffc (patch) | |
tree | eb72f344ee6c3d9b80a7ecc079ea79e9fba8676d /sccomp/source/solver/ParticelSwarmOptimization.hxx | |
parent | Initial commit. (diff) | |
download | libreoffice-upstream.tar.xz libreoffice-upstream.zip |
Adding upstream version 1:7.0.4.upstream/1%7.0.4upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to '')
-rw-r--r-- | sccomp/source/solver/ParticelSwarmOptimization.hxx | 179 |
1 files changed, 179 insertions, 0 deletions
diff --git a/sccomp/source/solver/ParticelSwarmOptimization.hxx b/sccomp/source/solver/ParticelSwarmOptimization.hxx new file mode 100644 index 000000000..ec76474dd --- /dev/null +++ b/sccomp/source/solver/ParticelSwarmOptimization.hxx @@ -0,0 +1,179 @@ +/* -*- 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 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: */ |