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DetSchedsLpChecker: Trying a slightly different encoding.

tempestpy_adaptions
Tim Quatmann 6 years ago
parent
bcd4c359b7
commit
9adf712883
1 changed files with 29 additions and 8 deletions
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  1. 35
      src/storm/modelchecker/multiobjective/deterministicScheds/DeterministicSchedsLpChecker.cpp

35
src/storm/modelchecker/multiobjective/deterministicScheds/DeterministicSchedsLpChecker.cpp
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@ -28,7 +28,7 @@ namespace storm {
template <typename ModelType, typename GeometryValueType> template <typename ModelType, typename GeometryValueType>
void DeterministicSchedsLpChecker<ModelType, GeometryValueType>::setCurrentWeightVector(std::vector<GeometryValueType> const& weightVector) { void DeterministicSchedsLpChecker<ModelType, GeometryValueType>::setCurrentWeightVector(std::vector<GeometryValueType> const& weightVector) {
STORM_LOG_ASSERT(!weightVector.empty(), "Setting an empty weight vector is not supported.");
STORM_LOG_ASSERT(weightVector.size() == objectiveHelper.size(), "Setting a weight vector with invalid number of entries.");
swLpBuild.start(); swLpBuild.start();
if (!currentWeightVector.empty()) { if (!currentWeightVector.empty()) {
// Pop information of the current weight vector. // Pop information of the current weight vector.
@ -36,13 +36,18 @@ namespace storm {
lpModel->update(); lpModel->update();
currentObjectiveVariables.clear(); currentObjectiveVariables.clear();
} }
currentWeightVector = weightVector; currentWeightVector = weightVector;
lpModel->push(); lpModel->push();
// set up objective function for the given weight vector // set up objective function for the given weight vector
for (uint64_t objIndex = 0; objIndex < initialStateResults.size(); ++objIndex) { for (uint64_t objIndex = 0; objIndex < initialStateResults.size(); ++objIndex) {
currentObjectiveVariables.push_back(lpModel->addUnboundedContinuousVariable("w_" + std::to_string(objIndex), storm::utility::convertNumber<ValueType>(weightVector[objIndex]))); currentObjectiveVariables.push_back(lpModel->addUnboundedContinuousVariable("w_" + std::to_string(objIndex), storm::utility::convertNumber<ValueType>(weightVector[objIndex])));
lpModel->addConstraint("", currentObjectiveVariables.back().getExpression() == initialStateResults[objIndex]);
if (objectiveHelper[objIndex].minimizing()) {
lpModel->addConstraint("", currentObjectiveVariables.back().getExpression() == -initialStateResults[objIndex]);
} else {
lpModel->addConstraint("", currentObjectiveVariables.back().getExpression() == initialStateResults[objIndex]);
}
} }
lpModel->update(); lpModel->update();
swLpBuild.stop(); swLpBuild.stop();
@ -117,7 +122,7 @@ namespace storm {
for (uint64_t choice = 0; choice < numChoices; ++choice) { for (uint64_t choice = 0; choice < numChoices; ++choice) {
localChoices.push_back(lpModel->addBoundedIntegerVariable("c" + std::to_string(state) + "_" + std::to_string(choice), 0, 1).getExpression()); localChoices.push_back(lpModel->addBoundedIntegerVariable("c" + std::to_string(state) + "_" + std::to_string(choice), 0, 1).getExpression());
} }
lpModel->addConstraint("", storm::expressions::sum(localChoices).reduceNesting() >= one);
lpModel->addConstraint("", storm::expressions::sum(localChoices).reduceNesting() == one);
choiceVars.insert(choiceVars.end(), localChoices.begin(), localChoices.end()); choiceVars.insert(choiceVars.end(), localChoices.begin(), localChoices.end());
} }
} }
@ -145,6 +150,7 @@ namespace storm {
if (schedulerIndependentStates.find(state) != schedulerIndependentStates.end()) { if (schedulerIndependentStates.find(state) != schedulerIndependentStates.end()) {
continue; continue;
} }
storm::expressions::Expression stateValue;
uint64_t numChoices = model.getNumberOfChoices(state); uint64_t numChoices = model.getNumberOfChoices(state);
uint64_t choiceOffset = model.getTransitionMatrix().getRowGroupIndices()[state]; uint64_t choiceOffset = model.getTransitionMatrix().getRowGroupIndices()[state];
for (uint64_t choice = 0; choice < numChoices; ++choice) { for (uint64_t choice = 0; choice < numChoices; ++choice) {
@ -163,14 +169,29 @@ namespace storm {
} }
choiceValue = choiceValue.simplify().reduceNesting(); choiceValue = choiceValue.simplify().reduceNesting();
if (numChoices == 1) { if (numChoices == 1) {
lpModel->addConstraint("", stateVars[state] == choiceValue);
stateValue = choiceValue;
} else { } else {
auto choiceValVar = lpModel->addBoundedContinuousVariable("x" + std::to_string(objIndex) + "_" + std::to_string(state) + "_" + std::to_string(choice), objectiveHelper[objIndex].getLowerValueBoundAtState(env, state), objectiveHelper[objIndex].getUpperValueBoundAtState(env, state)).getExpression();
uint64_t globalChoiceIndex = model.getTransitionMatrix().getRowGroupIndices()[state] + choice; uint64_t globalChoiceIndex = model.getTransitionMatrix().getRowGroupIndices()[state] + choice;
storm::expressions::Expression maxDiff = lpModel->getConstant(objectiveHelper[objIndex].getUpperValueBoundAtState(env, state) - objectiveHelper[objIndex].getLowerValueBoundAtState(env, state)) * (one - choiceVars[globalChoiceIndex]);
lpModel->addConstraint("", stateVars[state] - choiceValue <= maxDiff);
lpModel->addConstraint("", choiceValue - stateVars[state] <= maxDiff);
storm::expressions::Expression upperValueBoundAtChoice = lpModel->getConstant(objectiveHelper[objIndex].getUpperValueBoundAtState(env, state));
if (objectiveHelper[objIndex].minimizing()) {
lpModel->addConstraint("", choiceValVar + (upperValueBoundAtChoice * (one - choiceVars[globalChoiceIndex])) >= choiceValue);
} else {
lpModel->addConstraint("", choiceValVar <= choiceValue);
lpModel->addConstraint("", choiceValVar <= upperValueBoundAtChoice * choiceVars[globalChoiceIndex]);
}
if (choice == 0) {
stateValue = choiceValVar;
} else {
stateValue = stateValue + choiceValVar;
}
// Alternative encoding: (Then the sum of the choiceVars also has to be >= one (instead of == one)
//storm::expressions::Expression maxDiff = lpModel->getConstant(objectiveHelper[objIndex].getUpperValueBoundAtState(env, state) - objectiveHelper[objIndex].getLowerValueBoundAtState(env, state)) * (one - choiceVars[globalChoiceIndex]);
//lpModel->addConstraint("", stateVars[state] - choiceValVar <= maxDiff);
//lpModel->addConstraint("", choiceValVar - stateVars[state] <= maxDiff);
} }
} }
lpModel->addConstraint("", stateVars[state] <= stateValue);
} }
} }
lpModel->update(); lpModel->update();

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