diff --git a/src/storm/solver/SymbolicMinMaxLinearEquationSolver.cpp b/src/storm/solver/SymbolicMinMaxLinearEquationSolver.cpp
index 037179e2c..177be55c3 100644
--- a/src/storm/solver/SymbolicMinMaxLinearEquationSolver.cpp
+++ b/src/storm/solver/SymbolicMinMaxLinearEquationSolver.cpp
@@ -305,7 +305,7 @@ namespace storm {
             bool converged = false;
         
             // Choose initial scheduler.
-            storm::dd::Bdd<DdType> scheduler = this->hasInitialScheduler() ? this->getInitialScheduler() : this->A.sumAbstract(this->columnMetaVariables).maxAbstractRepresentative(this->choiceVariables);
+            storm::dd::Bdd<DdType> scheduler = this->hasInitialScheduler() ? this->getInitialScheduler() : (this->A.sumAbstract(this->columnMetaVariables).notZero() || b.notZero()).existsAbstractRepresentative(this->choiceVariables);
             
             // Initialize linear equation solver.
             // It should be at least as precise as this solver.
diff --git a/src/storm/utility/graph.cpp b/src/storm/utility/graph.cpp
index c12ca39e5..a2716ba8d 100644
--- a/src/storm/utility/graph.cpp
+++ b/src/storm/utility/graph.cpp
@@ -895,7 +895,7 @@ namespace storm {
                 
                 uint_fast64_t iterations = 0;
                 while (!frontier.isZero()) {
-                    storm::dd::Bdd<Type> statesAndChoicesWithProbabilityGreater0E = statesWithProbabilityGreater0E.inverseRelationalProductWithExtendedRelation(transitionMatrix, model.getRowVariables(), model.getColumnVariables());
+                    storm::dd::Bdd<Type> statesAndChoicesWithProbabilityGreater0E = frontier.inverseRelationalProductWithExtendedRelation(transitionMatrix, model.getRowVariables(), model.getColumnVariables());
                     frontier = phiStates && statesAndChoicesWithProbabilityGreater0E.existsAbstract(model.getNondeterminismVariables()) && !statesWithProbabilityGreater0E;
                     scheduler = scheduler || (frontier && statesAndChoicesWithProbabilityGreater0E).existsAbstractRepresentative(model.getNondeterminismVariables());
                     statesWithProbabilityGreater0E |= frontier;