def preprocess_bundles(self,
bundles=None,
force_preprocess_bundle_objective=False,
force_preprocess_bundle_constraints=False):
# TODO: Does this import need to be delayed because
# it is in a plugins subdirectory
from pyomo.solvers.plugins.solvers.persistent_solver import \
PersistentSolver
start_time = time.time()
if len(self._bundle_instances) == 0:
raise RuntimeError(
"Unable to preprocess scenario bundles. Bundling "
"does not seem to be activated.")
if bundles is None:
bundles = self._bundle_instances.keys()
if self.get_option("verbose"):
print("Preprocessing %s bundles" % len(bundles))
preprocess_bundle_objective = 0b01
preprocess_bundle_constraints = 0b10
for bundle_name in bundles:
preprocess_bundle = 0
solver = self._bundle_solvers[bundle_name]
persistent_solver_in_use = isinstance(solver, PersistentSolver)
bundle_ef_instance = self._bundle_instances[bundle_name]
if persistent_solver_in_use and \
(not solver.has_instance()):
assert self._bundle_first_preprocess[bundle_name]
solver.set_instance(bundle_ef_instance)
self._bundle_first_preprocess[bundle_name] = False
for scenario_name in self._bundle_scenarios[bundle_name]:
self._scenario_solvers[scenario_name].set_instance(
self._scenario_instances[scenario_name])
# We've preprocessed the instance, reset the relevant flags
self._scenario_first_preprocess[scenario_name] = False
self.clear_update_flags(scenario_name)
self.clear_fixed_variables(scenario_name)
self.clear_freed_variables(scenario_name)
else:
if persistent_solver_in_use:
assert not self._bundle_first_preprocess[bundle_name]
for scenario_name in self._bundle_scenarios[bundle_name]:
if self.objective_updated[scenario_name]:
preprocess_bundle |= preprocess_bundle_objective
if ((len(self.fixed_variables[scenario_name]) > 0) or \
(len(self.freed_variables[scenario_name]) > 0)) and \
self.get_option("preprocess_fixed_variables"):
preprocess_bundle |= \
preprocess_bundle_objective | \
preprocess_bundle_constraints
if self._bundle_first_preprocess[bundle_name]:
preprocess_bundle |= \
preprocess_bundle_objective | \
preprocess_bundle_constraints
self._bundle_first_preprocess[bundle_name] = False
if persistent_solver_in_use:
# also preprocess on the scenario solver
scenario_solver = self._scenario_solvers[scenario_name]
isinstance(scenario_solver, PersistentSolver)
self._preprocess_scenario(scenario_name,
scenario_solver)
self._preprocess_scenario(scenario_name, solver)
# We've preprocessed the instance, reset the relevant flags
self._scenario_first_preprocess[scenario_name] = False
self.clear_update_flags(scenario_name)
self.clear_fixed_variables(scenario_name)
self.clear_freed_variables(scenario_name)
if force_preprocess_bundle_objective:
preprocess_bundle |= preprocess_bundle_objective
if force_preprocess_bundle_constraints:
preprocess_bundle |= preprocess_bundle_constraints
if preprocess_bundle:
if persistent_solver_in_use:
assert solver.has_instance()
if preprocess_bundle & preprocess_bundle_objective:
obj_count = 0
for obj in bundle_ef_instance.component_data_objects(
ctype=Objective,
descend_into=False,
active=True):
obj_count += 1
if obj_count > 1:
raise RuntimeError(
"Persistent solver interface only "
"supports a single active objective.")
solver.set_objective(obj)
if preprocess_bundle & preprocess_bundle_constraints:
# we assume the bundle constraints are just simple
# linking constraints (e.g., no SOSConstraints)
for con in bundle_ef_instance.component_data_objects(
ctype=Constraint,
descend_into=False,
active=True):
solver.remove_constraint(con)
solver.add_constraint(con)
else:
if solver.problem_format == ProblemFormat.nl:
idMap = {}
if preprocess_bundle & preprocess_bundle_objective:
ampl_preprocess_block_objectives(
bundle_ef_instance, idMap=idMap)
if preprocess_bundle & preprocess_bundle_constraints:
ampl_preprocess_block_constraints(
bundle_ef_instance, idMap=idMap)
else:
idMap = {}
if preprocess_bundle & preprocess_bundle_objective:
canonical_preprocess_block_objectives(
bundle_ef_instance, idMap=idMap)
if preprocess_bundle & preprocess_bundle_constraints:
canonical_preprocess_block_constraints(
bundle_ef_instance, idMap=idMap)
end_time = time.time()
if self.get_option("output_times"):
print("Bundle preprocessing time=%.2f seconds" %
(end_time - start_time))
def preprocess_scenario_instance(scenario_instance,
instance_variables_fixed,
instance_variables_freed,
instance_user_constraints_modified,
instance_ph_constraints_modified,
instance_ph_constraints,
instance_objective_modified,
preprocess_fixed_variables,
solver):
persistent_solver_in_use = isinstance(solver, PersistentSolver)
if (not instance_objective_modified) and \
(not instance_variables_fixed) and \
(not instance_variables_freed) and \
(not instance_ph_constraints_modified) and \
(not instance_user_constraints_modified):
# the condition of "nothing modified" should only be triggered
# at PH iteration 0. instances are already preprocessed
# following construction, and there isn't any augmentation of
# the objective function yet.
return
if instance_objective_modified:
# if only the objective changed, there is minimal work to do.
if solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_objectives(scenario_instance)
else:
canonical_preprocess_block_objectives(scenario_instance)
if persistent_solver_in_use and solver.instance_compiled():
solver.compile_objective(scenario_instance)
if (instance_variables_fixed or instance_variables_freed) and \
(preprocess_fixed_variables):
if solver.problem_format() == ProblemFormat.nl:
ampl_expression_preprocessor({}, model=scenario_instance)
else:
canonical_expression_preprocessor({}, model=scenario_instance)
# We've preprocessed the entire instance, no point in checking
# anything else
return
if (instance_variables_fixed or instance_variables_freed) and \
(persistent_solver_in_use):
# it can be the case that the solver plugin no longer has an
# instance compiled, depending on what state the solver plugin
# is in relative to the instance. if this is the case, just
# don't compile the variable bounds.
if solver.instance_compiled():
variables_to_change = \
instance_variables_fixed + instance_variables_freed
solver.compile_variable_bounds(scenario_instance,
vars_to_update=variables_to_change)
if instance_user_constraints_modified:
if solver.problem_format() == ProblemFormat.nl:
idMap = {}
for block in scenario_instance.block_data_objects(active=True,
descend_into=True):
ampl_preprocess_block_constraints(block,
idMap=idMap)
else:
idMap = {}
for block in scenario_instance.block_data_objects(active=True,
descend_into=True):
canonical_preprocess_block_constraints(block,
idMap=idMap)
elif instance_ph_constraints_modified:
# only pre-process the piecewise constraints
if solver.problem_format() == ProblemFormat.nl:
idMap = {}
for constraint_name in instance_ph_constraints:
ampl_preprocess_constraint(
scenario_instance,
getattr(scenario_instance, constraint_name),
idMap=idMap)
else:
idMap = {}
for constraint_name in instance_ph_constraints:
canonical_preprocess_constraint(
scenario_instance,
getattr(scenario_instance, constraint_name),
idMap=idMap)
def preprocess_scenario_instance(
scenario_instance, instance_variables_fixed, instance_variables_freed,
instance_user_constraints_modified, instance_ph_constraints_modified,
instance_ph_constraints, instance_objective_modified,
preprocess_fixed_variables, solver):
persistent_solver_in_use = isinstance(solver, PersistentSolver)
if (not instance_objective_modified) and \
(not instance_variables_fixed) and \
(not instance_variables_freed) and \
(not instance_ph_constraints_modified) and \
(not instance_user_constraints_modified):
# the condition of "nothing modified" should only be triggered
# at PH iteration 0. instances are already preprocessed
# following construction, and there isn't any augmentation of
# the objective function yet.
return
if instance_objective_modified:
# if only the objective changed, there is minimal work to do.
if solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_objectives(scenario_instance)
else:
canonical_preprocess_block_objectives(scenario_instance)
if persistent_solver_in_use and solver.instance_compiled():
solver.compile_objective(scenario_instance)
if (instance_variables_fixed or instance_variables_freed) and \
(preprocess_fixed_variables):
if solver.problem_format() == ProblemFormat.nl:
ampl_expression_preprocessor({}, model=scenario_instance)
else:
canonical_expression_preprocessor({}, model=scenario_instance)
# We've preprocessed the entire instance, no point in checking
# anything else
return
if (instance_variables_fixed or instance_variables_freed) and \
(persistent_solver_in_use):
# it can be the case that the solver plugin no longer has an
# instance compiled, depending on what state the solver plugin
# is in relative to the instance. if this is the case, just
# don't compile the variable bounds.
if solver.instance_compiled():
variables_to_change = \
instance_variables_fixed + instance_variables_freed
solver.compile_variable_bounds(scenario_instance,
vars_to_update=variables_to_change)
if instance_user_constraints_modified:
if solver.problem_format() == ProblemFormat.nl:
idMap = {}
for block in scenario_instance.block_data_objects(
active=True, descend_into=True):
ampl_preprocess_block_constraints(block, idMap=idMap)
else:
idMap = {}
for block in scenario_instance.block_data_objects(
active=True, descend_into=True):
canonical_preprocess_block_constraints(block, idMap=idMap)
elif instance_ph_constraints_modified:
# only pre-process the piecewise constraints
if solver.problem_format() == ProblemFormat.nl:
idMap = {}
for constraint_name in instance_ph_constraints:
ampl_preprocess_constraint(scenario_instance,
getattr(scenario_instance,
constraint_name),
idMap=idMap)
else:
idMap = {}
for constraint_name in instance_ph_constraints:
canonical_preprocess_constraint(scenario_instance,
getattr(
scenario_instance,
constraint_name),
idMap=idMap)
def preprocess_bundles(self,
bundles=None,
force_preprocess_bundle_objective=False,
force_preprocess_bundle_constraints=False):
start_time = time.time()
if len(self._bundle_instances) == 0:
raise RuntimeError(
"Unable to preprocess scenario bundles. Bundling "
"does not seem to be activated.")
if bundles is None:
bundles = self._bundle_instances.keys()
if self.get_option("verbose"):
print("Preprocessing %s bundles" % len(bundles))
preprocess_bundle_objective = 0b01
preprocess_bundle_constraints = 0b10
for bundle_name in bundles:
preprocess_bundle = 0
solver = self._bundle_solvers[bundle_name]
for scenario_name in self._bundle_scenarios[bundle_name]:
if self.objective_updated[scenario_name]:
preprocess_bundle |= preprocess_bundle_objective
if ((len(self.fixed_variables[scenario_name]) > 0) or \
(len(self.freed_variables[scenario_name]) > 0)) and \
self.get_option("preprocess_fixed_variables"):
preprocess_bundle |= \
preprocess_bundle_objective | \
preprocess_bundle_constraints
if self._bundle_first_preprocess[bundle_name]:
preprocess_bundle |= \
preprocess_bundle_objective | \
preprocess_bundle_constraints
self._bundle_first_preprocess[bundle_name] = False
self._preprocess_scenario(scenario_name, solver)
# We've preprocessed the instance, reset the relevant flags
self.clear_update_flags(scenario_name)
self.clear_fixed_variables(scenario_name)
self.clear_freed_variables(scenario_name)
if force_preprocess_bundle_objective:
preprocess_bundle |= preprocess_bundle_objective
if force_preprocess_bundle_constraints:
preprocess_bundle |= preprocess_bundle_constraints
if preprocess_bundle:
bundle_ef_instance = \
self._bundle_instances[bundle_name]
if solver.problem_format == ProblemFormat.nl:
idMap = {}
if preprocess_bundle & preprocess_bundle_objective:
ampl_preprocess_block_objectives(bundle_ef_instance,
idMap=idMap)
if preprocess_bundle & preprocess_bundle_constraints:
ampl_preprocess_block_constraints(bundle_ef_instance,
idMap=idMap)
else:
idMap = {}
if preprocess_bundle & preprocess_bundle_objective:
canonical_preprocess_block_objectives(
bundle_ef_instance,
idMap=idMap)
if preprocess_bundle & preprocess_bundle_constraints:
canonical_preprocess_block_constraints(
bundle_ef_instance,
idMap=idMap)
end_time = time.time()
if self.get_option("output_times"):
print("Bundle preprocessing time=%.2f seconds"
% (end_time - start_time))
def _preprocess_scenario(self, scenario_name, solver):
# TODO: Does this import need to be delayed because
# it is in a plugins subdirectory
from pyomo.solvers.plugins.solvers.persistent_solver import \
PersistentSolver
assert scenario_name in self._scenario_instance
scenario_objective_active = self._scenario_objective[scenario_name].active
# because the preprocessor will skip the scenario objective if it is
# part of a bundle and not active
self._scenario_objective[scenario_name].activate()
def _cleanup():
if not scenario_objective_active:
self._scenario_objective[scenario_name].deactivate()
scenario_instance = self._scenario_instance[scenario_name]
instance_fixed_variables = self.fixed_variables[scenario_name]
instance_freed_variables = self.freed_variables[scenario_name]
instance_all_constraints_updated = \
self.all_constraints_updated[scenario_name]
instance_constraints_updated_list = \
self.constraints_updated_list[scenario_name]
instance_objective_updated = self.objective_updated[scenario_name]
persistent_solver_in_use = isinstance(solver, PersistentSolver)
if (not instance_objective_updated) and \
(not instance_fixed_variables) and \
(not instance_freed_variables) and \
(not instance_all_constraints_updated) and \
(len(instance_constraints_updated_list) == 0):
if persistent_solver_in_use:
assert solver.has_instance()
# instances are already preproccessed, nothing
# needs to be done
if self.get_option("verbose"):
print("No preprocessing necessary for scenario %s"
% (scenario_name))
_cleanup()
return
if (instance_fixed_variables or instance_freed_variables) and \
self.get_option("preprocess_fixed_variables"):
if self.get_option("verbose"):
print("Running full preprocessing for scenario %s"
% (scenario_name))
if solver.problem_format() == ProblemFormat.nl:
ampl_expression_preprocessor({}, model=scenario_instance)
else:
canonical_expression_preprocessor({}, model=scenario_instance)
# We've preprocessed the entire instance, no point in checking
# anything else
_cleanup()
return
if instance_objective_updated:
if self.get_option("verbose"):
print("Preprocessing objective for scenario %s"
% (scenario_name))
# if only the objective changed, there is minimal work to do.
if solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_objectives(scenario_instance)
else:
canonical_preprocess_block_objectives(scenario_instance)
if persistent_solver_in_use and solver.has_instance():
obj_count = 0
for obj in scenario_instance.component_data_objects(ctype=Objective, descend_into=True, active=True):
obj_count += 1
if obj_count > 1:
raise RuntimeError('Persistent solver interface only supports a single active objective.')
solver.set_objective(obj)
if (instance_fixed_variables or instance_freed_variables) and \
(persistent_solver_in_use):
if self.get_option("verbose"):
print("Compiling fixed status updates in persistent solver "
"for scenario %s" % (scenario_name))
# it can be the case that the solver plugin no longer has an
# instance compiled, depending on what state the solver plugin
# is in relative to the instance. if this is the case, just
# don't compile the variable bounds.
if solver.has_instance():
variables_to_change = \
instance_fixed_variables + instance_freed_variables
for var in variables_to_change:
solver.update_var(var)
if instance_all_constraints_updated:
if self.get_option("verbose"):
print("Preprocessing all constraints for scenario %s"
% (scenario_name))
if solver.problem_format() == ProblemFormat.nl:
idMap = {}
for block in scenario_instance.block_data_objects(
active=True,
descend_into=True):
ampl_preprocess_block_constraints(block, idMap=idMap)
else:
idMap = {}
for block in scenario_instance.block_data_objects(
active=True,
descend_into=True):
canonical_preprocess_block_constraints(block, idMap=idMap)
elif len(instance_constraints_updated_list) > 0:
# TODO
assert not persistent_solver_in_use
if self.get_option("verbose"):
print("Preprocessing constraint list (size=%s) for "
"scenario %s" % (len(instance_constraints_updated_list),
scenario_name))
idMap = {}
repn_name = None
repn_func = None
if solver.problem_format() == ProblemFormat.nl:
repn_name = "_ampl_repn"
repn_func = generate_ampl_repn
else:
repn_name = "_canonical_repn"
repn_func = generate_canonical_repn
for constraint_data in instance_constraints_updated_list:
if isinstance(constraint_data, LinearCanonicalRepn):
continue
block = constraint_data.parent_block()
# Get/Create the ComponentMap for the repn storage
if not hasattr(block, repn_name):
setattr(block, repn_name, ComponentMap())
getattr(block, repn_name)[constraint_data] = \
repn_func(constraint_data.body, idMap=idMap)
if persistent_solver_in_use and \
(not solver.has_instance()):
solver.set_instance(
scenario_instance,
symbolic_solver_labels=self.get_option("symbolic_solver_labels"),
output_fixed_variable_bounds=not self.get_option("preprocess_fixed_variables"))
_cleanup()
def get_modified_instance( ph, scenario_tree, scenario_or_bundle, **options):
# Find the model
if scenario_tree.contains_bundles():
model = ph._bundle_binding_instance_map[scenario_or_bundle._name]
else:
model = ph._instances[scenario_or_bundle._name]
b = model.component('_interscenario_plugin')
if b is not None:
return model
#
# We need to add the interscenario information to this model
#
model._interscenario_plugin = b = Block()
# Save our options
#
b.epsilon = options.pop('epsilon')
b.cut_scale = options.pop('cut_scale')
b.allow_slack = options.pop('allow_slack')
b.enable_rho = options.pop('enable_rho')
b.enable_cuts = options.pop('enable_cuts')
assert( len(options) == 0 )
# Information for generating cuts
#
b.cutlist = ConstraintList()
b.abs_int_vars = VarList(within=NonNegativeIntegers)
b.abs_binary_vars = VarList(within=Binary)
# Note: the var_ids are on the ORIGINAL scenario models
rootNode = scenario_tree.findRootNode()
var_ids = list(iterkeys(rootNode._variable_datas))
# Right now, this is hard-coded for 2-stage problems - so we only
# need to worry about the variables from the root node. These
# variables should exist on all scenarios. Set up a (trivial)
# equality constraint for each variable:
# var == current_value{param} + separation_variable{var, fixed=0}
b.STAGE1VAR = _S1V = Set(initialize=var_ids)
b.separation_variables = _sep = Var( _S1V, dense=True )
b.fixed_variable_values = _param = Param(_S1V, mutable=True, initialize=0)
b.rho = weakref.ref(model.component('PHRHO_%s' % rootNode._name))
b.weights = weakref.ref(model.component('PHWEIGHT_%s' % rootNode._name))
if b.allow_slack:
for idx in _sep:
_sep[idx].setlb(-b.epsilon)
_sep[idx].setub(b.epsilon)
else:
_sep.fix(0)
_cuidBuffer = {}
_src = b.local_stage1_varmap = {}
for i in _S1V:
# Note indexing: for each 1st stage var, pick an arbitrary
# (first) scenario and return the variable (and not it's
# probability)
_cuid = ComponentUID(rootNode._variable_datas[i][0][0], _cuidBuffer)
_src[i] = weakref.ref(_cuid.find_component_on(model))
#_base_src[i] = weakref.ref(_cuid.find_component_on(base_model))
def _set_var_value(b, i):
return _param[i] + _sep[i] - _src[i]() == 0
b.fixed_variables_constraint \
= _con = Constraint( _S1V, rule=_set_var_value )
#
# TODO: When we get the duals of the first-stage variables, do we
# want the dual WRT the original objective, or the dual WRT the
# augmented objective?
#
# Move the objective to a standardized place so we can easily find it later
if PYOMO_4_0:
_orig_objective = list( x[2] for x in model.all_component_data(
Objective, active=True, descend_into=True ) )
else:
_orig_objective = list( model.component_data_objects(
Objective, active=True, descend_into=True ) )
assert(len(_orig_objective) == 1)
_orig_objective = _orig_objective[0]
b.original_obj = weakref.ref(_orig_objective)
# add (and deactivate) the objective for the infeasibility
# separation problem.
b.separation_obj = Objective(
expr= sum( _sep[i]**2 for i in var_ids ),
sense = minimize )
# Make sure we get dual information
if 'dual' not in model:
# Export and import floating point data
model.dual = Suffix(direction=Suffix.IMPORT_EXPORT)
#if 'rc' not in model:
# model.rc = Suffix(direction=Suffix.IMPORT_EXPORT)
if FALLBACK_ON_BRUTE_FORCE_PREPROCESS:
model.preprocess()
else:
if ph._solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_constraints(b)
else:
_map = {}
canonical_preprocess_block_constraints(b, _map)
# Note: we wait to deactivate the objective until after we
# preprocess so that the obective is correctly processed.
b.separation_obj.deactivate()
# (temporarily) deactivate the fixed stage-1 variables
_con.deactivate()
toc("InterScenario: generated modified problem instance")
return model
def preprocess_scenario_instance(
scenario_instance, instance_variables_fixed, instance_variables_freed,
instance_user_constraints_modified, instance_ph_constraints_modified,
instance_ph_constraints, instance_objective_modified,
preprocess_fixed_variables, solver):
# TODO: Does this import need to be delayed because
# it is in a plugins subdirectory
from pyomo.solvers.plugins.solvers.persistent_solver import \
PersistentSolver
persistent_solver_in_use = isinstance(solver, PersistentSolver)
if (not instance_objective_modified) and \
(not instance_variables_fixed) and \
(not instance_variables_freed) and \
(not instance_ph_constraints_modified) and \
(not instance_user_constraints_modified):
# the condition of "nothing modified" should only be triggered
# at PH iteration 0. instances are already preprocessed
# following construction, and there isn't any augmentation of
# the objective function yet.
return
if instance_objective_modified:
# if only the objective changed, there is minimal work to do.
if solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_objectives(scenario_instance)
else:
canonical_preprocess_block_objectives(scenario_instance)
if persistent_solver_in_use and solver.has_instance():
obj_count = 0
for obj in scenario_instance.component_data_objects(
ctype=Objective, descend_into=True, active=True):
obj_count += 1
if obj_count > 1:
raise RuntimeError(
'Persistent solver interface only supports a single objective.'
)
solver.set_objective(obj)
if (instance_variables_fixed or instance_variables_freed) and \
(preprocess_fixed_variables):
if solver.problem_format() == ProblemFormat.nl:
ampl_expression_preprocessor({}, model=scenario_instance)
else:
canonical_expression_preprocessor({}, model=scenario_instance)
# We've preprocessed the entire instance, no point in checking
# anything else
return
if (instance_variables_fixed or instance_variables_freed) and \
(persistent_solver_in_use):
# it can be the case that the solver plugin no longer has an
# instance compiled, depending on what state the solver plugin
# is in relative to the instance. if this is the case, just
# don't compile the variable bounds.
if solver.has_instance():
variables_to_change = \
instance_variables_fixed + instance_variables_freed
for var_name, var_index in variables_to_change:
solver.update_var(
scenario_instance.find_component(var_name)[var_index])
if instance_user_constraints_modified:
if solver.problem_format() == ProblemFormat.nl:
idMap = {}
for block in scenario_instance.block_data_objects(
active=True, descend_into=True):
ampl_preprocess_block_constraints(block, idMap=idMap)
else:
idMap = {}
for block in scenario_instance.block_data_objects(
active=True, descend_into=True):
canonical_preprocess_block_constraints(block, idMap=idMap)
elif instance_ph_constraints_modified:
# only pre-process the piecewise constraints
if solver.problem_format() == ProblemFormat.nl:
idMap = {}
for constraint_name in instance_ph_constraints:
ampl_preprocess_constraint(scenario_instance,
getattr(scenario_instance,
constraint_name),
idMap=idMap)
else:
idMap = {}
for constraint_name in instance_ph_constraints:
canonical_preprocess_constraint(scenario_instance,
getattr(
scenario_instance,
constraint_name),
idMap=idMap)
def add_new_cuts( ph, scenario_tree, scenario_or_bundle,
feasibility_cuts, incumbent_cuts, resolve ):
# Find the model
m = get_modified_instance(ph, scenario_tree, scenario_or_bundle)
_block = m._interscenario_plugin
epsilon = _block.epsilon
cut_scale = _block.cut_scale
# Add the cuts to the ConstraintList on the model
_cutlist = _block.cutlist
_src = _block.local_stage1_varmap
for cut_obj, cut in feasibility_cuts:
expr = sum(
2 * (_sep*(1-cut_scale))
* (_src[i]() - (_par+_sep*(1-cut_scale)))
for i, (_sep, _par) in iteritems(cut)
if abs(_sep) > epsilon*max(1,_par)
)
if expr is not 0:
_cutlist.add( expr >= 0 )
for cut in incumbent_cuts:
_int_binaries = []
for vid, val in iteritems(cut[1]):
# Deal with integer variables
# b + c >= z
# b <= M*y
# c <= M*(1-y)
# x - val = c - b
# b,c >= 0
b = _block.abs_int_vars.add()
c = _block.abs_int_vars.add()
z = _block.abs_binary_vars.add()
y = _block.abs_binary_vars.add()
_cutlist.add( b + c >= z )
_cutlist.add( b <= _src[vid]().ub * y )
_cutlist.add( c <= _src[vid]().ub * (1-y) )
_cutlist.add( _src[vid]() - val == c - b )
_int_binaries.append( z )
_cutlist.add( sum(_int_binaries) + sum(
_src[vid]() if val<0.5 else (1-_src[vid]())
for vid,val in iteritems(cut[0]) ) >= 1 )
if FALLBACK_ON_BRUTE_FORCE_PREPROCESS:
m.preprocess()
else:
if ph._solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_constraints(_block)
else:
_map = {}
canonical_preprocess_block_constraints(_block,_map)
if resolve:
results = ph._solver.solve(m, warmstart=True)
ss = results.solver.status
tc = results.solver.termination_condition
#self.timeInSolver += results['Solver'][0]['Time']
if ss == SolverStatus.ok and tc in _acceptable_termination_conditions:
if PYOMO_4_0:
m.load(results)
else:
m.solutions.load_from(results)
_src = _block.local_stage1_varmap
return (
# Note: _src is {id: weakref} and original_obj is a
# weakref; so dereference weakref before computing value
dict((_id, value(_var())) for _id, _var in iteritems(_src)),
value(_block.original_obj()) )
else:
return None
def solve_fixed_scenario_solutions(
ph, scenario_tree, scenario_or_bundle,
scenario_solutions, **model_options ):
model = get_modified_instance(
ph, scenario_tree, scenario_or_bundle, **model_options )
_block = model._interscenario_plugin
_param = _block.fixed_variable_values
_sep = _block.separation_variables
_con = _block.fixed_variables_constraint
# We need to know which scenarios are local to this instance ... so
# we don't waste time repeating work.
if scenario_tree.contains_bundles():
local_scenarios = scenario_or_bundle._scenario_names
else:
local_scenarios = [ scenario_or_bundle._name ]
ipopt = SolverFactory("ipopt")
#
# Turn off RHO!
#
_saved_rho_values = _block.rho().extract_values()
_block.rho().store_values(0)
# Enable the constraints to fix the Stage 1 variables:
_con.activate()
# Solve each solution here and cache the resulting objective
cutlist = []
obj_values = []
dual_values = []
for var_values, scenario_name_list in scenario_solutions:
local = False
for scenario in local_scenarios:
if scenario in scenario_name_list:
local = True
break
if local:
# Here is where we could save some time and not repeat work
# ... for now I am being lazy and re-solving so that we get
# the dual values, etc for this scenario as well. If nothing
# else, it makes averaging easier.
pass
assert( len(var_values) == len(_param) )
for var_id, var_value in iteritems(var_values):
_param[var_id] = var_value
# TODO: We only need to update the CanonicalRepn for the binding
# constraints ... so we could save a LOT of time by not
# preprocessing the whole model.
#
if FALLBACK_ON_BRUTE_FORCE_PREPROCESS:
model.preprocess()
else:
if ph._solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_constraints(_block)
else:
var_id_map = {}
canonical_preprocess_block_constraints(_block, var_id_map)
toc("preprocessed scenario %s" % ( scenario_or_bundle._name, ))
output_buffer = StringIO()
pyutilib.misc.setup_redirect(output_buffer)
try:
results = ph._solver.solve(model, tee=True) # warmstart=True)
except:
logger.warning("Exception raised solving the interscenario "
"evaluation subproblem")
logger.warning("Solver log:\n%s" % output_buffer.getvalue())
raise
finally:
pyutilib.misc.reset_redirect()
toc("solved solution from scenario set %s on scenario %s" %
( scenario_name_list, scenario_or_bundle._name, ))
ss = results.solver.status
tc = results.solver.termination_condition
#self.timeInSolver += results['Solver'][0]['Time']
if ss == SolverStatus.ok and tc in _acceptable_termination_conditions:
state = 0 #'FEASIBLE'
if PYOMO_4_0:
model.load(results)
else:
model.solutions.load_from(results)
#
# Turn off W, recompute the objective
#
_saved_w_values = _block.weights().extract_values()
_block.weights().store_values(0)
obj_values.append(value(_block.original_obj()))
_block.weights().store_values(_saved_w_values)
# NOTE: Getting the dual values resolves the model
# (potentially relaxing second state variables.
if _block.enable_rho:
dual_values.append( get_dual_values(ph._solver, model) )
else:
dual_values.append(None)
cutlist.append(". ")
elif True or tc in _infeasible_termination_conditions:
state = 1 #'INFEASIBLE'
obj_values.append(None)
dual_values.append(None)
if _block.enable_cuts:
cut = solve_separation_problem(ph._solver, model, True)
if cut == '????':
if ph._solver.problem_format() != ProblemFormat.nl:
ampl_preprocess_block_constraints(_block)
cut = solve_separation_problem(ipopt, model, False)
else:
cut = "X "
cutlist.append( cut )
toc("solved separation problem for solution from scenario set "
"%s on scenario %s" %
( scenario_name_list, scenario_or_bundle._name, ))
else:
state = 2 #'NONOPTIMAL'
obj_values.append(None)
dual_values.append(None)
cutlist.append("? ")
logger.warning("Solving the interscenario evaluation "
"subproblem failed (%s)." % (state,) )
logger.warning("Solver log:\n%s" % output_buffer.getvalue())
#
# Turn RHO, W back on!
#
_block.weights().store_values(_saved_w_values)
_block.rho().store_values(_saved_rho_values)
# Disable the constraints to fix the Stage 1 variables:
_con.deactivate()
return obj_values, dual_values, cutlist
def solve_separation_problem(solver, model, fallback):
xfrm = TransformationFactory('core.relax_discrete')
if PYOMO_4_0:
xfrm.apply(model, inplace=True)
else:
xfrm.apply_to(model)
_block = model._interscenario_plugin
# Switch objectives
_block.original_obj().deactivate()
_block.separation_obj.activate()
#_block.separation_variables.unfix()
_par = _block.fixed_variable_values
_sep = _block.separation_variables
allow_slack = _block.allow_slack
if allow_slack:
epsilon = _block.epsilon
for idx in _sep:
_sep[idx].setlb(None)
_sep[idx].setub(None)
else:
_sep.unfix()
# Note: preprocessing is only necessary if we are changing a
# fixed/freed variable.
if FALLBACK_ON_BRUTE_FORCE_PREPROCESS:
model.preprocess()
else:
if solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_objectives(_block)
ampl_preprocess_block_constraints(_block)
else:
_map = {}
canonical_preprocess_block_objectives(_block,_map)
canonical_preprocess_block_constraints(_block,_map)
#SOLVE
output_buffer = StringIO()
pyutilib.misc.setup_redirect(output_buffer)
try:
results = solver.solve(model, tee=True)
except:
logger.warning("Exception raised solving the interscenario "
"evaluation subproblem")
logger.warning("Solver log:\n%s" % output_buffer.getvalue())
raise
finally:
pyutilib.misc.reset_redirect()
ss = results.solver.status
tc = results.solver.termination_condition
#self.timeInSolver += results['Solver'][0]['Time']
if ss == SolverStatus.ok and tc in _acceptable_termination_conditions:
state = ''
if PYOMO_4_0:
model.load(results)
else:
model.solutions.load_from(results)
elif tc in _infeasible_termination_conditions:
state = 'INFEASIBLE'
ans = "!!!!"
else:
state = 'NONOPTIMAL'
ans = "????"
if state:
if fallback:
#logger.warning("Initial attempt to solve the interscenario cut "
# "separation subproblem failed with the default "
# "solver (%s)." % (state,) )
pass
else:
logger.warning("Solving the interscenario cut separation "
"subproblem failed (%s)." % (state,) )
logger.warning("Solver log:\n%s" % output_buffer.getvalue())
else:
cut = dict((vid, (value(_sep[vid]), value(_par[vid])))
for vid in _block.STAGE1VAR)
obj = value(_block.separation_obj)
ans = (math.sqrt(obj), cut)
output_buffer.close()
# Restore the objective
_block.original_obj().activate()
_block.separation_obj.deactivate()
# Turn off the separation variables
if allow_slack:
for idx in _sep:
_sep[idx].setlb(-epsilon)
_sep[idx].setub(epsilon)
else:
_sep.fix(0)
if PYOMO_4_0:
xfrm.apply(model, inplace=True, undo=True)
else:
xfrm.apply_to(model, undo=True)
if FALLBACK_ON_BRUTE_FORCE_PREPROCESS:
pass
else:
if solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_objectives(_block)
else:
_map = {}
canonical_preprocess_block_objectives(_block,_map)
return ans
def get_dual_values(solver, model):
if id(model) not in get_dual_values.discrete_stage2_vars:
# 1st attempt to get duals: we need to see if the model has
# discrete variables (solvers won't give duals if there are
# still active discrete variables)
try:
get_dual_values.discrete_stage2_vars[id(model)] = False
return get_dual_values(solver, model)
except:
get_dual_values.discrete_stage2_vars[id(model)] = True
# Find the discrete variables to populate the list
return get_dual_values(solver, model)
duals = {}
_con = model._interscenario_plugin.fixed_variables_constraint
if get_dual_values.discrete_stage2_vars[id(model)]:
# Fix all discrete variables
xfrm = TransformationFactory('core.relax_discrete')
if PYOMO_4_0:
xfrm.apply(model, inplace=True)
else:
xfrm.apply_to(model)
# Note: preprocessing is only necessary if we are changing a
# fixed/freed variable.
if FALLBACK_ON_BRUTE_FORCE_PREPROCESS:
model.preprocess()
else:
if solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_constraints(model._interscenario_plugin)
else:
_map = {}
canonical_preprocess_block_constraints(
model._interscenario_plugin, _map )
#SOLVE
results = solver.solve(model, warmstart=True)
ss = results.solver.status
tc = results.solver.termination_condition
#self.timeInSolver += results['Solver'][0]['Time']
if ss == SolverStatus.ok and tc in _acceptable_termination_conditions:
state = ''
elif tc in _infeasible_termination_conditions:
state = 'INFEASIBLE'
else:
state = 'NONOPTIMAL'
if state:
logger.warning(
"Resolving subproblem model with relaxed second-stage "
"discrete variables failed (%s). "
"Dual values not available." % (state,) )
else:
# Get the duals
if PYOMO_4_0:
model.load(results)
else:
model.solutions.load_from(results)
#model.dual.pprint()
for varid in model._interscenario_plugin.STAGE1VAR:
duals[varid] = model.dual[_con[varid]]
# Free the discrete second-stage variables
if PYOMO_4_0:
xfrm.apply(model, inplace=True, undo=True)
else:
xfrm.apply_to(model, undo=True)
else:
# return the duals
for varid in model._interscenario_plugin.STAGE1VAR:
duals[varid] = model.dual[_con[varid]]
return duals
def _preprocess_scenario(self, scenario_name, solver):
assert scenario_name in self._scenario_instance
scenario_objective_active = self._scenario_objective[
scenario_name].active
# because the preprocessor will skip the scenario objective if it is
# part of a bundle and not active
self._scenario_objective[scenario_name].activate()
def _cleanup():
if not scenario_objective_active:
self._scenario_objective[scenario_name].deactivate()
scenario_instance = self._scenario_instance[scenario_name]
instance_fixed_variables = self.fixed_variables[scenario_name]
instance_freed_variables = self.freed_variables[scenario_name]
instance_all_constraints_updated = \
self.all_constraints_updated[scenario_name]
instance_constraints_updated_list = \
self.constraints_updated_list[scenario_name]
instance_objective_updated = self.objective_updated[scenario_name]
persistent_solver_in_use = isinstance(solver, PersistentSolver)
if (not instance_objective_updated) and \
(not instance_fixed_variables) and \
(not instance_freed_variables) and \
(not instance_all_constraints_updated) and \
(len(instance_constraints_updated_list) == 0):
# instances are already preproccessed, nothing
# needs to be done
if self._options.verbose:
print("No preprocessing necessary for scenario %s" %
(scenario_name))
_cleanup()
return
if (instance_fixed_variables or instance_freed_variables) and \
(self._options.preprocess_fixed_variables):
if self._options.verbose:
print("Running full preprocessing for scenario %s" %
(scenario_name))
if solver.problem_format() == ProblemFormat.nl:
ampl_expression_preprocessor({}, model=scenario_instance)
else:
canonical_expression_preprocessor({}, model=scenario_instance)
# We've preprocessed the entire instance, no point in checking
# anything else
_cleanup()
return
if instance_objective_updated:
if self._options.verbose:
print("Preprocessing objective for scenario %s" %
(scenario_name))
# if only the objective changed, there is minimal work to do.
if solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_objectives(scenario_instance)
else:
canonical_preprocess_block_objectives(scenario_instance)
if persistent_solver_in_use and \
solver.instance_compiled():
solver.compile_objective(scenario_instance)
if (instance_fixed_variables or instance_freed_variables) and \
(persistent_solver_in_use):
if self._options.verbose:
print("Compiling fixed status updates in persistent solver "
"for scenario %s" % (scenario_name))
# it can be the case that the solver plugin no longer has an
# instance compiled, depending on what state the solver plugin
# is in relative to the instance. if this is the case, just
# don't compile the variable bounds.
if solver.instance_compiled():
variables_to_change = \
instance_fixed_variables + instance_freed_variables
solver.compile_variable_bounds(
scenario_instance, vars_to_update=variables_to_change)
if instance_all_constraints_updated:
if self._options.verbose:
print("Preprocessing all constraints for scenario %s" %
(scenario_name))
if solver.problem_format() == ProblemFormat.nl:
idMap = {}
for block in scenario_instance.block_data_objects(
active=True, descend_into=True):
ampl_preprocess_block_constraints(block, idMap=idMap)
else:
idMap = {}
for block in scenario_instance.block_data_objects(
active=True, descend_into=True):
canonical_preprocess_block_constraints(block, idMap=idMap)
elif len(instance_constraints_updated_list) > 0:
if self._options.verbose:
print("Preprocessing constraint list (size=%s) for "
"scenario %s" %
(len(instance_constraints_updated_list), scenario_name))
idMap = {}
repn_name = None
repn_func = None
if solver.problem_format() == ProblemFormat.nl:
repn_name = "_ampl_repn"
repn_func = generate_ampl_repn
else:
repn_name = "_canonical_repn"
repn_func = generate_canonical_repn
for constraint_data in instance_constraints_updated_list:
if isinstance(constraint_data, LinearCanonicalRepn):
continue
block = constraint_data.parent_block()
# Get/Create the ComponentMap for the repn storage
if not hasattr(block, repn_name):
setattr(block, repn_name, ComponentMap())
getattr(block, repn_name)[constraint_data] = \
repn_func(constraint_data.body, idMap=idMap)
_cleanup()
def _preprocess_scenario(self, scenario_name, solver):
assert scenario_name in self._scenario_instance
scenario_objective_active = self._scenario_objective[scenario_name].active
# because the preprocessor will skip the scenario objective if it is
# part of a bundle and not active
self._scenario_objective[scenario_name].activate()
def _cleanup():
if not scenario_objective_active:
self._scenario_objective[scenario_name].deactivate()
scenario_instance = self._scenario_instance[scenario_name]
instance_fixed_variables = self.fixed_variables[scenario_name]
instance_freed_variables = self.freed_variables[scenario_name]
instance_all_constraints_updated = self.all_constraints_updated[scenario_name]
instance_constraints_updated_list = self.constraints_updated_list[scenario_name]
instance_objective_updated = self.objective_updated[scenario_name]
persistent_solver_in_use = isinstance(solver, PersistentSolver)
if (
(not instance_objective_updated)
and (not instance_fixed_variables)
and (not instance_freed_variables)
and (not instance_all_constraints_updated)
and (len(instance_constraints_updated_list) == 0)
):
if persistent_solver_in_use:
assert solver.instance_compiled()
# instances are already preproccessed, nothing
# needs to be done
if self._options.verbose:
print("No preprocessing necessary for scenario %s" % (scenario_name))
_cleanup()
return
if (instance_fixed_variables or instance_freed_variables) and (self._options.preprocess_fixed_variables):
if self._options.verbose:
print("Running full preprocessing for scenario %s" % (scenario_name))
if solver.problem_format() == ProblemFormat.nl:
ampl_expression_preprocessor({}, model=scenario_instance)
else:
canonical_expression_preprocessor({}, model=scenario_instance)
# We've preprocessed the entire instance, no point in checking
# anything else
_cleanup()
return
if instance_objective_updated:
if self._options.verbose:
print("Preprocessing objective for scenario %s" % (scenario_name))
# if only the objective changed, there is minimal work to do.
if solver.problem_format() == ProblemFormat.nl:
ampl_preprocess_block_objectives(scenario_instance)
else:
canonical_preprocess_block_objectives(scenario_instance)
if persistent_solver_in_use and solver.instance_compiled():
solver.compile_objective(scenario_instance)
if (instance_fixed_variables or instance_freed_variables) and (persistent_solver_in_use):
if self._options.verbose:
print("Compiling fixed status updates in persistent solver " "for scenario %s" % (scenario_name))
# it can be the case that the solver plugin no longer has an
# instance compiled, depending on what state the solver plugin
# is in relative to the instance. if this is the case, just
# don't compile the variable bounds.
if solver.instance_compiled():
variables_to_change = instance_fixed_variables + instance_freed_variables
solver.compile_variable_bounds(scenario_instance, vars_to_update=variables_to_change)
if instance_all_constraints_updated:
if self._options.verbose:
print("Preprocessing all constraints for scenario %s" % (scenario_name))
if solver.problem_format() == ProblemFormat.nl:
idMap = {}
for block in scenario_instance.block_data_objects(active=True, descend_into=True):
ampl_preprocess_block_constraints(block, idMap=idMap)
else:
idMap = {}
for block in scenario_instance.block_data_objects(active=True, descend_into=True):
canonical_preprocess_block_constraints(block, idMap=idMap)
elif len(instance_constraints_updated_list) > 0:
# TODO
assert not persistent_solver_in_use
if self._options.verbose:
print(
"Preprocessing constraint list (size=%s) for "
"scenario %s" % (len(instance_constraints_updated_list), scenario_name)
)
idMap = {}
repn_name = None
repn_func = None
if solver.problem_format() == ProblemFormat.nl:
repn_name = "_ampl_repn"
repn_func = generate_ampl_repn
else:
repn_name = "_canonical_repn"
repn_func = generate_canonical_repn
for constraint_data in instance_constraints_updated_list:
if isinstance(constraint_data, LinearCanonicalRepn):
continue
block = constraint_data.parent_block()
# Get/Create the ComponentMap for the repn storage
if not hasattr(block, repn_name):
setattr(block, repn_name, ComponentMap())
getattr(block, repn_name)[constraint_data] = repn_func(constraint_data.body, idMap=idMap)
if persistent_solver_in_use and (not solver.instance_compiled()):
solver.compile_instance(
scenario_instance,
symbolic_solver_labels=self._options.symbolic_solver_labels,
output_fixed_variable_bounds=not self._options.preprocess_fixed_variables,
)
_cleanup()
def preprocess_bundles(
self, bundles=None, force_preprocess_bundle_objective=False, force_preprocess_bundle_constraints=False
):
start_time = time.time()
if len(self._bundle_instances) == 0:
raise RuntimeError("Unable to preprocess scenario bundles. Bundling " "does not seem to be activated.")
if bundles is None:
bundles = self._bundle_instances.keys()
if self._options.verbose:
print("Preprocessing %s bundles" % len(bundles))
preprocess_bundle_objective = 0b01
preprocess_bundle_constraints = 0b10
for bundle_name in bundles:
preprocess_bundle = 0
solver = self._bundle_solvers[bundle_name]
for scenario_name in self._bundle_scenarios[bundle_name]:
if self.objective_updated[scenario_name]:
preprocess_bundle |= preprocess_bundle_objective
if (
(len(self.fixed_variables[scenario_name]) > 0) or (len(self.freed_variables[scenario_name]) > 0)
) and self._options.preprocess_fixed_variables:
preprocess_bundle |= preprocess_bundle_objective | preprocess_bundle_constraints
if self._bundle_first_preprocess[bundle_name]:
preprocess_bundle |= preprocess_bundle_objective | preprocess_bundle_constraints
self._bundle_first_preprocess[bundle_name] = False
self._preprocess_scenario(scenario_name, solver)
# We've preprocessed the instance, reset the relevant flags
self.clear_update_flags(scenario_name)
self.clear_fixed_variables(scenario_name)
self.clear_freed_variables(scenario_name)
if force_preprocess_bundle_objective:
preprocess_bundle |= preprocess_bundle_objective
if force_preprocess_bundle_constraints:
preprocess_bundle |= preprocess_bundle_constraints
if preprocess_bundle:
bundle_ef_instance = self._bundle_instances[bundle_name]
if solver.problem_format == ProblemFormat.nl:
idMap = {}
if preprocess_bundle & preprocess_bundle_objective:
ampl_preprocess_block_objectives(bundle_ef_instance, idMap=idMap)
if preprocess_bundle & preprocess_bundle_constraints:
ampl_preprocess_block_constraints(bundle_ef_instance, idMap=idMap)
else:
idMap = {}
if preprocess_bundle & preprocess_bundle_objective:
canonical_preprocess_block_objectives(bundle_ef_instance, idMap=idMap)
if preprocess_bundle & preprocess_bundle_constraints:
canonical_preprocess_block_constraints(bundle_ef_instance, idMap=idMap)
end_time = time.time()
if self._options.output_times:
print("Bundle preprocessing time=%.2f seconds" % (end_time - start_time))
