def create_child_candidate_from_assignment(self,candidate,assignment):
new_candidate = Candidate()
new_candidate.resolved_conflicts = candidate.resolved_conflicts.copy()
new_candidate.continuously_resolved_cycles = candidate.continuously_resolved_cycles.copy()
new_candidate.assignments_to_avoid = candidate.assignments_to_avoid.copy()
new_candidate.assigned_variables = candidate.assigned_variables.copy()
new_candidate.add_assignments(candidate.assignments)
if not new_candidate.add_assignment(assignment):
return None
new_candidate.add_temporal_relaxations(candidate.temporal_relaxations)
new_candidate.add_semantic_relaxations(candidate.semantic_relaxations)
# with this new assignment, find all available/unassigned variables
for variable in self.tpnu.decision_variables.values():
# it must not have been assigned
if not variable in new_candidate.assigned_variables:
# and the guard must have been satisfied
if len(variable.guards) == 0 or variable.guards <= new_candidate.assignments:
new_candidate.unassigned_variables.put(variable)
new_candidate.h += variable.optimal_utility
return new_candidate
def create_child_candidate_from_assignment(self, candidate, assignment):
new_candidate = Candidate()
new_candidate.resolved_conflicts = candidate.resolved_conflicts.copy()
new_candidate.continuously_resolved_cycles = candidate.continuously_resolved_cycles.copy(
)
new_candidate.assignments_to_avoid = candidate.assignments_to_avoid.copy(
)
new_candidate.assigned_variables = candidate.assigned_variables.copy()
new_candidate.add_assignments(candidate.assignments)
if not new_candidate.add_assignment(assignment):
return None
new_candidate.add_temporal_relaxations(candidate.temporal_relaxations)
new_candidate.add_semantic_relaxations(candidate.semantic_relaxations)
# with this new assignment, find all available/unassigned variables
for variable in self.tpnu.decision_variables.values():
# it must not have been assigned
if not variable in new_candidate.assigned_variables:
# and the guard must have been satisfied
if len(variable.guards
) == 0 or variable.guards <= new_candidate.assignments:
new_candidate.unassigned_variables.put(variable)
new_candidate.h += variable.optimal_utility
return new_candidate
def create_child_candidate_from_relaxations(self,
candidate,
relaxations=None,
allocations=None):
new_candidate = Candidate()
new_candidate.resolved_conflicts = candidate.resolved_conflicts.copy()
new_candidate.continuously_resolved_cycles = candidate.continuously_resolved_cycles.copy(
)
new_candidate.assignments_to_avoid = candidate.assignments_to_avoid.copy(
)
new_candidate.assigned_variables = candidate.assigned_variables.copy()
new_candidate.add_assignments(candidate.assignments)
# We do not need the following line as it adds duplicated relaxations to the
# new candidate.
# new_candidate.add_temporal_relaxations(candidate.temporal_relaxations)
# Add temporal relaxations
if relaxations is not None:
for relaxation in relaxations:
if not new_candidate.add_temporal_relaxation(relaxation):
return None
# Add temporal allocations
if allocations is not None:
for allocation in allocations:
if not new_candidate.add_temporal_allocation(allocation):
return None
new_candidate.add_semantic_relaxations(candidate.semantic_relaxations)
# find all available variables
for variable in self.tpnu.decision_variables.values():
# it must not have been assigned
if not variable in new_candidate.assigned_variables:
# and the guard must have been satisfied
if len(variable.guards
) == 0 or variable.guards <= new_candidate.assignments:
new_candidate.unassigned_variables.put(variable)
new_candidate.h += variable.optimal_utility
return new_candidate
def create_child_candidate_from_relaxations(self,candidate,relaxations=None,allocations=None):
new_candidate = Candidate()
new_candidate.resolved_conflicts = candidate.resolved_conflicts.copy()
new_candidate.continuously_resolved_cycles = candidate.continuously_resolved_cycles.copy()
new_candidate.assignments_to_avoid = candidate.assignments_to_avoid.copy()
new_candidate.assigned_variables = candidate.assigned_variables.copy()
new_candidate.add_assignments(candidate.assignments)
# We do not need the following line as it adds duplicated relaxations to the
# new candidate.
# new_candidate.add_temporal_relaxations(candidate.temporal_relaxations)
# Add temporal relaxations
if relaxations is not None:
for relaxation in relaxations:
if not new_candidate.add_temporal_relaxation(relaxation):
return None
# Add temporal allocations
if allocations is not None:
for allocation in allocations:
if not new_candidate.add_temporal_allocation(allocation):
return None
new_candidate.add_semantic_relaxations(candidate.semantic_relaxations)
# find all available variables
for variable in self.tpnu.decision_variables.values():
# it must not have been assigned
if not variable in new_candidate.assigned_variables:
# and the guard must have been satisfied
if len(variable.guards) == 0 or variable.guards <= new_candidate.assignments:
new_candidate.unassigned_variables.put(variable)
new_candidate.h += variable.optimal_utility
return new_candidate