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#include "storm/solver/LpMinMaxLinearEquationSolver.h"
#include "storm/utility/vector.h"
#include "storm/utility/macros.h"
#include "storm/exceptions/InvalidSettingsException.h"
#include "storm/exceptions/InvalidOperationException.h"
#include "storm/exceptions/UnexpectedException.h"
namespace storm {
namespace solver {
template<typename ValueType>
LpMinMaxLinearEquationSolver<ValueType>::LpMinMaxLinearEquationSolver(storm::storage::SparseMatrix<ValueType> const& A, std::unique_ptr<LinearEquationSolverFactory<ValueType>>&& linearEquationSolverFactory, std::unique_ptr<storm::utility::solver::LpSolverFactory<ValueType>>&& lpSolverFactory) : StandardMinMaxLinearEquationSolver<ValueType>(A, std::move(linearEquationSolverFactory)), lpSolverFactory(std::move(lpSolverFactory)) {
// Intentionally left empty.
}
template<typename ValueType>
LpMinMaxLinearEquationSolver<ValueType>::LpMinMaxLinearEquationSolver(storm::storage::SparseMatrix<ValueType>&& A, std::unique_ptr<LinearEquationSolverFactory<ValueType>>&& linearEquationSolverFactory, std::unique_ptr<storm::utility::solver::LpSolverFactory<ValueType>>&& lpSolverFactory) : StandardMinMaxLinearEquationSolver<ValueType>(std::move(A), std::move(linearEquationSolverFactory)), lpSolverFactory(std::move(lpSolverFactory)) {
// Intentionally left empty.
}
template<typename ValueType>
bool LpMinMaxLinearEquationSolver<ValueType>::solveEquations(OptimizationDirection dir, std::vector<ValueType>& x, std::vector<ValueType> const& b) const {
// Set up the LP solver
std::unique_ptr<storm::solver::LpSolver<ValueType>> solver = lpSolverFactory->create("");
solver->setOptimizationDirection(invert(dir));
// Create a variable for each row group
std::vector<storm::expressions::Variable> variables;
variables.reserve(this->A.getRowGroupCount());
for (uint64_t rowGroup = 0; rowGroup < this->A.getRowGroupCount(); ++rowGroup) {
if (this->lowerBound) {
if (this->upperBound) {
variables.push_back(solver->addBoundedContinuousVariable("x" + std::to_string(rowGroup), this->lowerBound.get(), this->upperBound.get(), storm::utility::one<ValueType>()));
} else {
variables.push_back(solver->addLowerBoundedContinuousVariable("x" + std::to_string(rowGroup), this->lowerBound.get(), storm::utility::one<ValueType>()));
}
} else {
if (this->upperBound) {
variables.push_back(solver->addUpperBoundedContinuousVariable("x" + std::to_string(rowGroup), this->upperBound.get(), storm::utility::one<ValueType>()));
} else {
variables.push_back(solver->addUnboundedContinuousVariable("x" + std::to_string(rowGroup), storm::utility::one<ValueType>()));
}
}
}
solver->update();
// Add a constraint for each row
for (uint64_t rowGroup = 0; rowGroup < this->A.getRowGroupCount(); ++rowGroup) {
for (uint64_t row = this->A.getRowGroupIndices()[rowGroup]; row < this->A.getRowGroupIndices()[rowGroup + 1]; ++row) {
storm::expressions::Expression rowConstraint = solver->getConstant(b[row]);
for (auto const& entry : this->A.getRow(row)) {
rowConstraint = rowConstraint + (solver->getConstant(entry.getValue()) * variables[entry.getColumn()].getExpression());
}
if (minimize(dir)) {
rowConstraint = variables[rowGroup].getExpression() <= rowConstraint;
} else {
rowConstraint = variables[rowGroup].getExpression() >= rowConstraint;
}
solver->addConstraint("", rowConstraint);
}
}
// Invoke optimization
solver->optimize();
STORM_LOG_THROW(!solver->isInfeasible(), storm::exceptions::UnexpectedException, "The MinMax equation system is infeasible.");
STORM_LOG_THROW(!solver->isUnbounded(), storm::exceptions::UnexpectedException, "The MinMax equation system is unbounded.");
STORM_LOG_THROW(solver->isOptimal(), storm::exceptions::UnexpectedException, "Unable to find optimal solution for MinMax equation system.");
// write the solution into the solution vector
STORM_LOG_ASSERT(x.size() == variables.size(), "Dimension of x-vector does not match number of varibales.");
auto xIt = x.begin();
auto vIt = variables.begin();
for (; xIt != x.end(); ++xIt, ++vIt) {
*xIt = solver->getContinuousValue(*vIt);
}
// If requested, we store the scheduler for retrieval.
if (this->isTrackSchedulerSet()) {
this->schedulerChoices = std::vector<uint_fast64_t>(this->A.getRowGroupCount());
for (uint64_t rowGroup = 0; rowGroup < this->A.getRowGroupCount(); ++rowGroup) {
uint64_t row = this->A.getRowGroupIndices()[rowGroup];
uint64_t optimalChoiceIndex = 0;
uint64_t currChoice = 0;
ValueType optimalGroupValue = this->A.multiplyRowWithVector(row, x) + b[row];
for (++row, ++currChoice; row < this->A.getRowGroupIndices()[rowGroup + 1]; ++row, ++currChoice) {
ValueType rowValue = this->A.multiplyRowWithVector(row, x) + b[row];
if ((minimize(dir) && rowValue < optimalGroupValue) || (maximize(dir) && rowValue > optimalGroupValue)) {
optimalGroupValue = rowValue;
optimalChoiceIndex = currChoice;
}
}
this->schedulerChoices.get()[rowGroup] = optimalChoiceIndex;
}
}
return true;
}
template<typename ValueType>
void LpMinMaxLinearEquationSolver<ValueType>::clearCache() const {
StandardMinMaxLinearEquationSolver<ValueType>::clearCache();
}
template<typename ValueType>
LpMinMaxLinearEquationSolverFactory<ValueType>::LpMinMaxLinearEquationSolverFactory(bool trackScheduler) : StandardMinMaxLinearEquationSolverFactory<ValueType>(MinMaxMethodSelection::LinearProgramming, trackScheduler), lpSolverFactory(std::make_unique<storm::utility::solver::LpSolverFactory<ValueType>>()) {
// Intentionally left empty
}
template<typename ValueType>
LpMinMaxLinearEquationSolverFactory<ValueType>::LpMinMaxLinearEquationSolverFactory(std::unique_ptr<storm::utility::solver::LpSolverFactory<ValueType>>&& lpSolverFactory, bool trackScheduler) : StandardMinMaxLinearEquationSolverFactory<ValueType>(MinMaxMethodSelection::LinearProgramming, trackScheduler), lpSolverFactory(std::move(lpSolverFactory)) {
// Intentionally left empty
}
template<typename ValueType>
LpMinMaxLinearEquationSolverFactory<ValueType>::LpMinMaxLinearEquationSolverFactory(std::unique_ptr<LinearEquationSolverFactory<ValueType>>&& linearEquationSolverFactory, std::unique_ptr<storm::utility::solver::LpSolverFactory<ValueType>>&& lpSolverFactory, bool trackScheduler) : StandardMinMaxLinearEquationSolverFactory<ValueType>(std::move(linearEquationSolverFactory), MinMaxMethodSelection::LinearProgramming, trackScheduler), lpSolverFactory(std::move(lpSolverFactory)) {
// Intentionally left empty
}
template<typename ValueType>
std::unique_ptr<MinMaxLinearEquationSolver<ValueType>> LpMinMaxLinearEquationSolverFactory<ValueType>::create(storm::storage::SparseMatrix<ValueType> const& matrix) const {
STORM_LOG_ASSERT(this->linearEquationSolverFactory, "Linear equation solver factory not initialized.");
STORM_LOG_ASSERT(this->lpSolverFactory, "Lp solver factory not initialized.");
std::unique_ptr<MinMaxLinearEquationSolver<ValueType>> result = std::make_unique<LpMinMaxLinearEquationSolver<ValueType>>(std::move(matrix), this->linearEquationSolverFactory->clone(), this->lpSolverFactory->clone());
result->setTrackScheduler(this->isTrackSchedulerSet());
return result;
}
template<typename ValueType>
std::unique_ptr<MinMaxLinearEquationSolver<ValueType>> LpMinMaxLinearEquationSolverFactory<ValueType>::create(storm::storage::SparseMatrix<ValueType>&& matrix) const {
STORM_LOG_ASSERT(this->linearEquationSolverFactory, "Linear equation solver factory not initialized.");
STORM_LOG_ASSERT(this->lpSolverFactory, "Lp solver factory not initialized.");
std::unique_ptr<MinMaxLinearEquationSolver<ValueType>> result = std::make_unique<LpMinMaxLinearEquationSolver<ValueType>>(std::move(matrix), this->linearEquationSolverFactory->clone(), this->lpSolverFactory->clone());
result->setTrackScheduler(this->isTrackSchedulerSet());
return result;
}
template<typename ValueType>
void LpMinMaxLinearEquationSolverFactory<ValueType>::setMinMaxMethod(MinMaxMethodSelection const& newMethod) {
STORM_LOG_THROW(newMethod == MinMaxMethodSelection::LinearProgramming, storm::exceptions::InvalidOperationException, "The factory can only create linear programming based MinMax solvers.");
MinMaxLinearEquationSolverFactory<ValueType>::setMinMaxMethod(newMethod);
}
template<typename ValueType>
void LpMinMaxLinearEquationSolverFactory<ValueType>::setMinMaxMethod(MinMaxMethod const& newMethod) {
STORM_LOG_THROW(newMethod == MinMaxMethod::LinearProgramming, storm::exceptions::InvalidOperationException, "The factory can only create linear programming based MinMax solvers.");
MinMaxLinearEquationSolverFactory<ValueType>::setMinMaxMethod(newMethod);
}
template class LpMinMaxLinearEquationSolver<double>;
template class LpMinMaxLinearEquationSolverFactory<double>;
#ifdef STORM_HAVE_CARL
template class LpMinMaxLinearEquationSolver<storm::RationalNumber>;
template class LpMinMaxLinearEquationSolverFactory<storm::RationalNumber>;
#endif
}
}