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:
_map = {}
preprocess_block_objectives(_block, idMap=_map)
preprocess_block_constraints(_block, idMap=_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:
_map = {}
preprocess_block_objectives(_block, idMap=_map)
return ans
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:
_map = {}
preprocess_block_objectives(_block, idMap=_map)
preprocess_block_constraints(_block, idMap=_map)
#SOLVE
output_buffer = StringIO()
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:
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:
_map = {}
preprocess_block_objectives(_block, idMap=_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:
_map = {}
preprocess_block_constraints(
model._interscenario_plugin, idMap=_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 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:
_map = {}
preprocess_block_constraints(model._interscenario_plugin,
idMap=_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
