Пример #1
0
    def __init__(self, manager, *args, **kwds):
        import pyomo.solvers.plugins.smanager.pyro
        super(ExtensiveFormAlgorithm, self).__init__(*args, **kwds)

        # TODO: after PH moves over to the new code
        #if not isinstance(manager, ScenarioTreeManager):
        #    raise TypeError("ExtensiveFormAlgorithm requires an instance of the "
        #                    "ScenarioTreeManager interface as the "
        #                    "second argument")
        if not manager.initialized:
            raise ValueError("ExtensiveFormAlgorithm requires a scenario tree "
                             "manager that has been fully initialized")

        self._manager = manager
        self.instance = None
        self._solver_manager = None
        self._solver = None

        # The following attributes will be modified by the
        # solve() method. For users that are scripting, these
        # can be accessed after the solve() method returns.
        # They will be reset each time solve() is called.
        ############################################
        self.objective = None
        self.gap = None
        self.termination_condition = None
        self.termination_message = None
        self.solver_status = None
        self.solution_status = None
        self.solver_results = None
        self.time = None
        self.pyomo_time = None
        ############################################

        # apparently the SolverFactory does not have sane
        # behavior when the solver name is None
        if self.get_option("solver") is None:
            raise ValueError("The 'solver' option can not be None")
        self._solver = SolverFactory(self.get_option("solver"),
                                     solver_io=self.get_option("solver_io"))
        if isinstance(self._solver, UnknownSolver):
            raise ValueError("Failed to create solver of type=" +
                             self.get_option("solver") +
                             " for use in extensive form solve")

        solver_manager_type = self.get_option("solver_manager")
        if solver_manager_type == "phpyro":
            print("*** WARNING ***: PHPyro is not a supported solver "
                  "manager type for the extensive-form solver. "
                  "Falling back to serial.")
            solver_manager_type = 'serial'

        self._solver_manager = SolverManagerFactory(
            solver_manager_type,
            host=self.get_option("solver_manager_pyro_host"),
            port=self.get_option("solver_manager_pyro_port"))
        if self._solver_manager is None:
            raise ValueError("Failed to create solver manager of type=" +
                             self.get_option("solver") +
                             " for use in extensive form solve")
Пример #2
0
    def __init__(self, *args, **kwds):
        if self.__class__ is _ScenarioTreeManagerSolverWorker:
            raise NotImplementedError(
                "%s is an abstract class for subclassing" % self.__class__)

        super(_ScenarioTreeManagerSolverWorker, self).__init__(*args, **kwds)

        assert self.manager is not None

        # solver related objects
        self._scenario_solvers = {}
        self._bundle_solvers = {}
        self._preprocessor = None
        self._solver_manager = None

        # there are situations in which it is valuable to snapshot /
        # store the solutions associated with the scenario
        # instances. for example, when one wants to use a warm-start
        # from a particular iteration solve, following a modification
        # and re-solve of the problem instances in a user-defined
        # callback. the following nested dictionary is intended to
        # serve that purpose. The nesting is dependent on whether
        # bundling and or phpyro is in use
        self._cached_solutions = {}
        self._cached_scenariotree_solutions = {}

        #
        # initialize the preprocessor
        #
        self._preprocessor = None
        if not self.get_option("disable_advanced_preprocessing"):
            self._preprocessor = ScenarioTreePreprocessor(
                self._options, options_prefix=self._options_prefix)
        assert self._manager.preprocessor is None
        self._manager.preprocessor = self._preprocessor

        #
        # initialize the solver manager
        #
        self._solver_manager = SolverManagerFactory(
            self.get_option("solver_manager"),
            host=self.get_option('solver_manager_pyro_host'),
            port=self.get_option('solver_manager_pyro_port'))
        for scenario in self.manager.scenario_tree._scenarios:
            assert scenario._instance is not None
            solver = self._scenario_solvers[scenario.name] = \
                SolverFactory(self.get_option("solver"),
                              solver_io=self.get_option("solver_io"))
            if self._preprocessor is not None:
                self._preprocessor.add_scenario(scenario, scenario._instance,
                                                solver)
        for bundle in self.manager.scenario_tree._scenario_bundles:
            solver = self._bundle_solvers[bundle.name] = \
                SolverFactory(self.get_option("solver"),
                              solver_io=self.get_option("solver_io"))
            bundle_instance = \
                self.manager._bundle_binding_instance_map[bundle.name]
            if self._preprocessor is not None:
                self._preprocessor.add_bundle(bundle, bundle_instance, solver)
Пример #3
0
Файл: ef.py Проект: Pyomo/pyomo
    def __init__(self, manager, *args, **kwds):
        import pyomo.solvers.plugins.smanager.pyro
        super(ExtensiveFormAlgorithm, self).__init__(*args, **kwds)

        # TODO: after PH moves over to the new code
        #if not isinstance(manager, ScenarioTreeManager):
        #    raise TypeError("ExtensiveFormAlgorithm requires an instance of the "
        #                    "ScenarioTreeManager interface as the "
        #                    "second argument")
        if not manager.initialized:
            raise ValueError("ExtensiveFormAlgorithm requires a scenario tree "
                             "manager that has been fully initialized")

        self._manager = manager
        self.instance = None
        self._solver_manager = None
        self._solver = None

        # The following attributes will be modified by the
        # solve() method. For users that are scripting, these
        # can be accessed after the solve() method returns.
        # They will be reset each time solve() is called.
        ############################################
        self.objective = None
        self.gap = None
        self.termination_condition = None
        self.termination_message = None
        self.solver_status = None
        self.solution_status = None
        self.solver_results = None
        self.time = None
        self.pyomo_time = None
        ############################################

        # apparently the SolverFactory does not have sane
        # behavior when the solver name is None
        if self.get_option("solver") is None:
            raise ValueError("The 'solver' option can not be None")
        self._solver = SolverFactory(self.get_option("solver"),
                                     solver_io=self.get_option("solver_io"))
        if isinstance(self._solver, UnknownSolver):
            raise ValueError("Failed to create solver of type="+
                             self.get_option("solver")+
                             " for use in extensive form solve")

        solver_manager_type = self.get_option("solver_manager")
        if solver_manager_type == "phpyro":
            print("*** WARNING ***: PHPyro is not a supported solver "
                  "manager type for the extensive-form solver. "
                  "Falling back to serial.")
            solver_manager_type = 'serial'

        self._solver_manager = SolverManagerFactory(
            solver_manager_type,
            host=self.get_option("solver_manager_pyro_host"),
            port=self.get_option("solver_manager_pyro_port"))
        if self._solver_manager is None:
            raise ValueError("Failed to create solver manager of type="
                             +self.get_option("solver")+
                             " for use in extensive form solve")
def pyomo_solver(model, solver, config, neos=False):
    """Solve the continuous NLP by discretizing it using backward finite difference and pyomo solvers
    
    Arguments:
        model {pyomo model} -- a concrete model build using Pyomo
        solver {string}     -- Solver used for the optimization problem. For e.g. ipopt
        config{yaml}        -- configurations of the setting
        neos  {bool}        -- Use the neos solver if True
    """

    # time variables
    if model.tf < 1.0:
        N = config['freq']
    else:
        N = int(round(model.tf * config['freq']))

    # finite difference discretization
    # pyo.TransformationFactory('dae.finite_difference').apply_to(model, wrt=model.t, nfe=N, scheme='BACKWARD')

    # direct collocation
    pyo.TransformationFactory('dae.collocation').apply_to(model,
                                                          wrt=model.t,
                                                          nfe=N,
                                                          ncp=6)
    # if a particular variable has to be piecewise constant then uncomment the following and replace the var parameter in 'reduce_collocation_points'
    # pyo.TransformationFactory('dae.collocation').apply_to(model, wrt=model.t, nf=10, ncp=6).reduce_collocation_points(model, var=model.u, ncp=1, contset=model.t)

    if neos:
        print("Using NEOS with Pyomo")
        SolverManagerFactory('neos').solve(model, opt=solver).write()
    else:
        pyo.SolverFactory(solver).solve(model).write()

    return model
Пример #5
0
 def __init__(self, params):
     self.numScen = params.numScen
     self.mstX = params.x
     self.mstSita = params.sita
     sb_mdl = import_file("sub.py").model
     sub_insts = []
     global directory
     for s in range(self.numScen):
         sub_path = directory + "\\data\\ScenNode" + str(s + 1) + ".dat"
         sub_insts.append(
          sb_mdl.create_instance(name="sub"+str(s+1), \
                 filename=sub_path))
     solver_manager = SolverManagerFactory("serial")
     self.model = sb_mdl
     self.instance = sub_insts
     self.solver_manager = solver_manager
Пример #6
0
def run_path(data):
    #call solver
    opt = SolverFactory('cplex')
    solver_manager = SolverManagerFactory('pyro')
    #report_timing = True to see time taken for each model component
    inst = pmod.model.create_instance(data, report_timing=True)
    #fix variable I to be 0
    for (h, v, t) in inst.aux:
        inst.I[h, v, t].fix(0)
    #tee=True to trace the cplex process
    result = opt.solve(inst, tee=True, warmstart=True)
    inst.solutions.load_from(result)
    '''
    for (s,e) in inst.OD:
         for p in inst.P:
             for j in inst.N:
                for t in inst.TS:
                    if inst.q[s,e,p,j,t]() > 0:
                        print 'queue', s,e,p,j,t,inst.q[s,e,p,j,t]()
    '''
    for (s, e) in inst.OD:
        for p in inst.P:
            for j in inst.N:
                for t in inst.TS:
                    if inst.f[s, e, p, j, t]() > 0:
                        print >> f, 'outflow', s, e, p, j, t, inst.f[s, e, p,
                                                                     j, t]()
    '''
    for (s,e) in inst.OD:
        for p in inst.P:
            for j in inst.N:
                for t in inst.TS:
                    for v in inst.VS:
                        if inst.b[s,e,p,v,t,j]() > 0:
                            print 'board', s,e,p,v,t,j,inst.b[s,e,p,v,t,j]()
    '''
    print >> f, 'objective value', inst.obj()
    #result.write()
    inst.display()
    exec_time = time.time() - start_time
    print "execution time", exec_time, 's'
Пример #7
0
class ExtensiveFormAlgorithm(PySPConfiguredObject):
    @classmethod
    def _declare_options(cls, options=None):
        if options is None:
            options = PySPConfigBlock()

        safe_declare_unique_option(
            options,
            "cvar_weight",
            PySPConfigValue(
                1.0,
                domain=_domain_nonnegative,
                description=("The weight associated with the CVaR term in "
                             "the risk-weighted objective "
                             "formulation. If the weight is 0, then "
                             "*only* a non-weighted CVaR cost will appear "
                             "in the EF objective - the expected cost "
                             "component will be dropped. Default is 1.0."),
                doc=None,
                visibility=0),
            ap_group=_ef_group_label)
        safe_declare_unique_option(
            options,
            "generate_weighted_cvar",
            PySPConfigValue(
                False,
                domain=bool,
                description=("Add a weighted CVaR term to the "
                             "primary objective. Default is False."),
                doc=None,
                visibility=0),
            ap_group=_ef_group_label)
        safe_declare_unique_option(
            options,
            "risk_alpha",
            PySPConfigValue(
                0.95,
                domain=_domain_unit_interval,
                description=("The probability threshold associated with "
                             "CVaR (or any future) risk-oriented "
                             "performance metrics. Default is 0.95."),
                doc=None,
                visibility=0),
            ap_group=_ef_group_label)
        safe_declare_unique_option(
            options,
            "cc_alpha",
            PySPConfigValue(
                0.0,
                domain=_domain_unit_interval,
                description=("The probability threshold associated with a "
                             "chance constraint. The RHS will be one "
                             "minus this value. Default is 0."),
                doc=None,
                visibility=0),
            ap_group=_ef_group_label)
        safe_declare_unique_option(
            options,
            "cc_indicator_var",
            PySPConfigValue(
                None,
                domain=_domain_must_be_str,
                description=("The name of the binary variable to be used "
                             "to construct a chance constraint. Default "
                             "is None, which indicates no chance "
                             "constraint."),
                doc=None,
                visibility=0),
            ap_group=_ef_group_label)
        safe_declare_common_option(options, "solver")
        safe_declare_common_option(options, "solver_io")
        safe_declare_common_option(options, "solver_manager")
        safe_declare_common_option(options, "solver_options")
        safe_declare_common_option(options, "disable_warmstart")
        safe_declare_common_option(options, "solver_manager_pyro_host")
        safe_declare_common_option(options, "solver_manager_pyro_port")
        safe_declare_common_option(options, "solver_manager_pyro_shutdown")
        safe_declare_common_option(options,
                                   "verbose",
                                   ap_group=_ef_group_label)
        safe_declare_common_option(options,
                                   "output_times",
                                   ap_group=_ef_group_label)
        safe_declare_common_option(options,
                                   "output_solver_results",
                                   ap_group=_ef_group_label)

        return options

    def __enter__(self):
        return self

    def __exit__(self, *args):
        self.close()

    def close(self):
        self.destroy_ef()
        if self._solver_manager is not None:
            if isinstance(self._solver_manager,
                          pyomo.solvers.plugins.smanager.\
                          pyro.SolverManager_Pyro):
                if self.get_option("pyro_shutdown_workers"):
                    self._solver_manager.shutdown_workers()
        self._solver_manager = None
        self._manager = None

    def __init__(self, manager, *args, **kwds):
        import pyomo.solvers.plugins.smanager.pyro
        super(ExtensiveFormAlgorithm, self).__init__(*args, **kwds)

        # TODO: after PH moves over to the new code
        #if not isinstance(manager, ScenarioTreeManager):
        #    raise TypeError("ExtensiveFormAlgorithm requires an instance of the "
        #                    "ScenarioTreeManager interface as the "
        #                    "second argument")
        if not manager.initialized:
            raise ValueError("ExtensiveFormAlgorithm requires a scenario tree "
                             "manager that has been fully initialized")

        self._manager = manager
        self.instance = None
        self._solver_manager = None
        self._solver = None

        # The following attributes will be modified by the
        # solve() method. For users that are scripting, these
        # can be accessed after the solve() method returns.
        # They will be reset each time solve() is called.
        ############################################
        self.objective = None
        self.gap = None
        self.termination_condition = None
        self.termination_message = None
        self.solver_status = None
        self.solution_status = None
        self.solver_results = None
        self.time = None
        self.pyomo_time = None
        ############################################

        # apparently the SolverFactory does not have sane
        # behavior when the solver name is None
        if self.get_option("solver") is None:
            raise ValueError("The 'solver' option can not be None")
        self._solver = SolverFactory(self.get_option("solver"),
                                     solver_io=self.get_option("solver_io"))
        if isinstance(self._solver, UnknownSolver):
            raise ValueError("Failed to create solver of type=" +
                             self.get_option("solver") +
                             " for use in extensive form solve")

        solver_manager_type = self.get_option("solver_manager")
        if solver_manager_type == "phpyro":
            print("*** WARNING ***: PHPyro is not a supported solver "
                  "manager type for the extensive-form solver. "
                  "Falling back to serial.")
            solver_manager_type = 'serial'

        self._solver_manager = SolverManagerFactory(
            solver_manager_type,
            host=self.get_option("solver_manager_pyro_host"),
            port=self.get_option("solver_manager_pyro_port"))
        if self._solver_manager is None:
            raise ValueError("Failed to create solver manager of type=" +
                             self.get_option("solver") +
                             " for use in extensive form solve")

    def build_ef(self):
        self.destroy_ef()
        if self.get_option("verbose"):
            print("Creating extensive form instance")
        start_time = time.time()

        # then validate the associated parameters.
        generate_weighted_cvar = False
        cvar_weight = None
        risk_alpha = None
        if self.get_option("generate_weighted_cvar"):
            generate_weighted_cvar = True
            cvar_weight = self.get_option("cvar_weight")
            risk_alpha = self.get_option("risk_alpha")

        self.instance = create_ef_instance(
            self._manager.scenario_tree,
            verbose_output=self.get_option("verbose"),
            generate_weighted_cvar=generate_weighted_cvar,
            cvar_weight=cvar_weight,
            risk_alpha=risk_alpha,
            cc_indicator_var_name=self.get_option("cc_indicator_var"),
            cc_alpha=self.get_option("cc_alpha"))

        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to construct extensive form instance=%.2f seconds" %
                  (time.time() - start_time))

    def destroy_ef(self):
        if self.instance is not None:
            for scenario in self._manager.scenario_tree.scenarios:
                self.instance.del_component(scenario.name)
                scenario._instance_objective.activate()
        self.instance = None

    def write(self, filename):

        if self.instance is None:
            raise RuntimeError(
                "The extensive form instance has not been constructed."
                "Call the build_ef() method to construct it.")

        suf = os.path.splitext(filename)[1]
        if suf not in ['.nl', '.lp', '.mps']:
            if self._solver.problem_format() == ProblemFormat.cpxlp:
                filename += '.lp'
            elif self._solver.problem_format() == ProblemFormat.nl:
                filename += '.nl'
            elif self._solver.problem_format() == ProblemFormat.mps:
                filename += '.mps'
            else:
                raise ValueError("Could not determine output file format. "
                                 "No recognized ending suffix was provided "
                                 "and no format was indicated was by the "
                                 "--solver-io option.")

        start_time = time.time()
        print("Writing extensive form to file=" + filename)
        smap_id = write_ef(self.instance, filename,
                           self.get_option("symbolic_solver_labels"))

        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to write output file=%.2f seconds" %
                  (time.time() - start_time))

        return filename, smap_id

    def solve(self,
              check_status=True,
              exception_on_failure=True,
              output_solver_log=False,
              symbolic_solver_labels=False,
              keep_solver_files=False,
              io_options=None):
        # TODO: Does this import need to be delayed because
        #       it is in a plugins subdirectory
        from pyomo.solvers.plugins.solvers.persistent_solver import \
            PersistentSolver

        if self.instance is None:
            raise RuntimeError(
                "The extensive form instance has not been constructed."
                "Call the build_ef() method to construct it.")

        start_time = time.time()
        if self.get_option("verbose"):
            print("Queuing extensive form solve")

        self.objective = None
        self.gap = None
        self.bound = None
        self.termination_condition = None
        self.termination_message = None
        self.solver_status = None
        self.solution_status = None
        self.solver_results = None
        self.time = None
        self.pyomo_time = None

        if isinstance(self._solver, PersistentSolver):
            self._solver.compile_instance(
                self.instance, symbolic_solver_labels=symbolic_solver_labels)

        solve_kwds = {}
        solve_kwds['load_solutions'] = False
        if keep_solver_files:
            solve_kwds['keepfiles'] = True
        if symbolic_solver_labels:
            solve_kwds['symbolic_solver_labels'] = True
        if output_solver_log:
            solve_kwds['tee'] = True

        solver_options = self.get_option("solver_options")
        if len(solver_options) > 0:
            if type(solver_options) is tuple:
                solve_kwds["options"] = {}
                for name_val in solver_options:
                    assert "=" in name_val
                    name, val = name_val.split("=")
                    solve_kwds["options"][name.strip()] = val.strip()
            else:
                solve_kwds["options"] = solver_options

        if io_options is not None:
            solve_kwds.update(io_options)

        self.objective_sense = \
            find_active_objective(self.instance).sense

        if (not self.get_option("disable_warmstart")) and \
           (self._solver.warm_start_capable()):
            action_handle = self._solver_manager.queue(self.instance,
                                                       opt=self._solver,
                                                       warmstart=True,
                                                       **solve_kwds)
        else:
            action_handle = self._solver_manager.queue(self.instance,
                                                       opt=self._solver,
                                                       **solve_kwds)

        if self.get_option("verbose"):
            print("Waiting for extensive form solve")
        results = self._solver_manager.wait_for(action_handle)

        if self.get_option("verbose"):
            print("Done with extensive form solve - loading results")

        if self.get_option("output_solver_results"):
            print("Results for ef:")
            results.write(num=1)

        self.solver_results = results
        if hasattr(results.solver,"user_time") and \
           (not isinstance(results.solver.user_time,
                           UndefinedData)) and \
           (results.solver.user_time is not None):
            # the solve time might be a string, or might
            # not be - we eventually would like more
            # consistency on this front from the solver
            # plugins.
            self.time = \
                float(results.solver.user_time)
        elif hasattr(results.solver, "time"):
            self.time = \
                float(results.solver.time)
        else:
            self.time = None

        if hasattr(results, "pyomo_solve_time"):
            self.pyomo_time = \
                results.pyomo_solve_time
        else:
            self.pyomo_time = None

        self.termination_condition = \
            results.solver.termination_condition
        self.termination_message = None
        if hasattr(results.solver, "termination_message"):
            self.termination_message = results.solver.termination_message
        elif hasattr(results.solver, "message"):
            self.termination_message = results.solver.message
        self.solver_status = \
            results.solver.status

        if len(results.solution) > 0:
            assert len(results.solution) == 1

            results_sm = results._smap
            self.instance.solutions.load_from(results)

            solution0 = results.solution(0)
            if hasattr(solution0, "gap") and \
               (solution0.gap is not None) and \
               (not isinstance(solution0.gap,
                               UndefinedData)):
                self.gap = float(solution0.gap)
            else:
                self.gap = None

            self.solution_status = solution0.status

            if self.get_option("verbose"):
                print("Storing solution in scenario tree")

            for scenario in self._manager.scenario_tree.scenarios:
                scenario.update_solution_from_instance()
            self._manager.scenario_tree.snapshotSolutionFromScenarios()
            self.objective = self._manager.scenario_tree.\
                             findRootNode().\
                             computeExpectedNodeCost()
            if self.gap is not None:
                if self.objective_sense == pyomo.core.base.minimize:
                    self.bound = self.objective - self.gap
                else:
                    self.bound = self.objective + self.gap

        else:

            self.objective = None
            self.gap = None
            self.bound = None
            self.solution_status = None

        failure = False

        if check_status:
            if not ((self.solution_status == SolutionStatus.optimal) or \
                    (self.solution_status == SolutionStatus.feasible)):
                failure = True
                if self.get_option("verbose") or \
                   exception_on_failure:
                    msg = ("EF solve failed solution status check:\n"
                           "Solver Status: %s\n"
                           "Termination Condition: %s\n"
                           "Solution Status: %s\n" %
                           (self.solver_status, self.termination_condition,
                            self.solution_status))
                    if self.get_option("verbose"):
                        print(msg)
                    if exception_on_failure:
                        raise RuntimeError(msg)
        else:
            if self.get_option("verbose"):
                print("EF solve completed. Skipping status check.")

        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to solve and load results for the "
                  "extensive form=%.2f seconds" % (time.time() - start_time))

        return failure
Пример #8
0
# parallel.py
from __future__ import division
from pyomo.environ import *
from pyomo.opt import SolverFactory
from pyomo.opt.parallel import SolverManagerFactory
import sys

action_handle_map = {} # maps action handles to instances

# Create a solver
optsolver = SolverFactory('cplex')

# create a solver manager
# 'pyro' could be replaced with 'serial'
solver_manager = SolverManagerFactory('pyro')
if solver_manager is None:
    print "Failed to create solver manager."
    sys.exit(1)

#
# A simple model with binary variables and
# an empty constraint list.
#
model = AbstractModel()
model.n = Param(default=4)
model.x = Var(RangeSet(model.n), within=Binary)
def o_rule(model):
    return sum_product(model.x)
model.o = Objective(rule=o_rule)
model.c = ConstraintList()
Пример #9
0
    def __init__(self, manager, *args, **kwds):
        import pysp.pyro.smanager_pyro
        super(ExtensiveFormAlgorithm, self).__init__(*args, **kwds)

        # TODO: after PH moves over to the new code
        #if not isinstance(manager, ScenarioTreeManager):
        #    raise TypeError("ExtensiveFormAlgorithm requires an instance of the "
        #                    "ScenarioTreeManager interface as the "
        #                    "second argument")
        if not manager.initialized:
            raise ValueError("ExtensiveFormAlgorithm requires a scenario tree "
                             "manager that has been fully initialized")

        self._manager = manager
        self.instance = None
        self._solver_manager = None
        self._solver = None

        # The following attributes will be modified by the
        # solve() method. For users that are scripting, these
        # can be accessed after the solve() method returns.
        # They will be reset each time solve() is called.
        ############################################
        self.objective = undefined
        self.gap = undefined
        self.termination_condition = undefined
        self.solver_status = undefined
        self.solution_status = undefined
        self.solver_results = undefined
        self.pyomo_solve_time = undefined
        self.solve_time = undefined
        ############################################

        self._solver = SolverFactory(self.get_option("solver"),
                                     solver_io=self.get_option("solver_io"))
        if isinstance(self._solver, UnknownSolver):
            raise ValueError("Failed to create solver of type="+
                             self.get_option("solver")+
                             " for use in extensive form solve")
        if len(self.get_option("solver_options")) > 0:
            if self.get_option("verbose"):
                print("Initializing ef solver with options="
                      +str(list(self.get_option("solver_options"))))
            self._solver.set_options("".join(self.get_option("solver_options")))
        if self.get_option("mipgap") is not None:
            if (self.get_option("mipgap") < 0.0) or \
               (self.get_option("mipgap") > 1.0):
                raise ValueError("Value of the mipgap parameter for the EF "
                                 "solve must be on the unit interval; "
                                 "value specified="+str(self.get_option("mipgap")))
            self._solver.options.mipgap = float(self.get_option("mipgap"))

        solver_manager_type = self.get_option("solver_manager")
        if solver_manager_type == "phpyro":
            print("*** WARNING ***: PHPyro is not a supported solver "
                  "manager type for the extensive-form solver. "
                  "Falling back to serial.")
            solver_manager_type = 'serial'

        self._solver_manager = SolverManagerFactory(
            solver_manager_type,
            host=self.get_option("pyro_host"),
            port=self.get_option("pyro_port"))
        if self._solver_manager is None:
            raise ValueError("Failed to create solver manager of type="
                             +self.get_option("solver")+
                             " for use in extensive form solve")
Пример #10
0
class ExtensiveFormAlgorithm(PySPConfiguredObject):

    _declared_options = \
        PySPConfigBlock("Options declared for the "
                        "ExtensiveFormAlgorithm class")

    safe_declare_unique_option(
        _declared_options,
        "cvar_weight",
        PySPConfigValue(
            1.0,
            domain=_domain_nonnegative,
            description=(
                "The weight associated with the CVaR term in "
                "the risk-weighted objective "
                "formulation. If the weight is 0, then "
                "*only* a non-weighted CVaR cost will appear "
                "in the EF objective - the expected cost "
                "component will be dropped. Default is 1.0."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "generate_weighted_cvar",
        PySPConfigValue(
            False,
            domain=bool,
            description=(
                "Add a weighted CVaR term to the "
                "primary objective. Default is False."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "risk_alpha",
        PySPConfigValue(
            0.95,
            domain=_domain_unit_interval,
            description=(
                "The probability threshold associated with "
                "CVaR (or any future) risk-oriented "
                "performance metrics. Default is 0.95."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "cc_alpha",
        PySPConfigValue(
            0.0,
            domain=_domain_unit_interval,
            description=(
                "The probability threshold associated with a "
                "chance constraint. The RHS will be one "
                "minus this value. Default is 0."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "cc_indicator_var",
        PySPConfigValue(
            None,
            domain=_domain_must_be_str,
            description=(
                "The name of the binary variable to be used "
                "to construct a chance constraint. Default "
                "is None, which indicates no chance "
                "constraint."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "mipgap",
        PySPConfigValue(
            None,
            domain=_domain_unit_interval,
            description=(
                "Specifies the mipgap for the EF solve."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "solver",
        PySPConfigValue(
            "cplex",
            domain=_domain_must_be_str,
            description=(
                "Specifies the solver used to solve the "
                "extensive form model. Default is cplex."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "solver_io",
        PySPConfigValue(
            None,
            domain=_domain_must_be_str,
            description=(
                "The type of IO used to execute the "
                "solver. Different solvers support different "
                "types of IO, but the following are common "
                "options: lp - generate LP files, nl - "
                "generate NL files, python - direct Python "
                "interface, os - generate OSiL XML files."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "solver_manager",
        PySPConfigValue(
            'serial',
            domain=_domain_must_be_str,
            description=(
                "The type of solver manager used to "
                "coordinate solves. Default is serial."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "solver_options",
        PySPConfigValue(
            (),
            domain=_domain_tuple_of_str_or_dict,
            description=(
                "Persistent solver options used when "
                "solving the extensive form model. This "
                "option can be used multiple times from "
                "the command line to specify more than "
                "one solver option."
            ),
            doc=None,
            visibility=0),
        ap_kwds={'action': 'append'},
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "disable_warmstart",
        PySPConfigValue(
            False,
            domain=bool,
            description=(
                "Disable warm-start of EF solves. "
                "Default is False."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "pyro_host",
        PySPConfigValue(
            None,
            domain=_domain_must_be_str,
            description=(
                "The hostname to bind on when searching "
                "for a Pyro nameserver."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "pyro_port",
        PySPConfigValue(
            None,
            domain=_domain_nonnegative_integer,
            description=(
                "The port to bind on when searching for "
                "a Pyro nameserver."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "pyro_shutdown",
        PySPConfigValue(
            False,
            domain=bool,
            description=(
                "Attempt to shut down all Pyro-related components "
                "associated with the Pyro name server used by any scenario "
                "tree manager or solver manager. Components to shutdown "
                "include the name server, dispatch server, and any "
                "scenariotreeserver or pyro_mip_server processes. Note "
                "that if Pyro4 is in use the nameserver will always "
                "ignore this request."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "pyro_shutdown_workers",
        PySPConfigValue(
            False,
            domain=bool,
            description=(
                "Upon exit, send shutdown requests to all worker "
                "processes that were acquired through the dispatcher. "
                "This typically includes scenariotreeserver processes "
                "(used by the Pyro scenario tree manager) and pyro_mip_server "
                "processes (used by the Pyro solver manager). This leaves "
                "any dispatchers and namservers running as well as any "
                "processes registered with the dispather that were not "
                "acquired for work by this client."
            ),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "symbolic_solver_labels",
                               ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "output_solver_log",
                               ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "verbose",
                               ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "output_times",
                               ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "keep_solver_files",
                               ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "output_solver_results",
                               ap_group=_ef_group_label)

    def __enter__(self):
        return self

    def __exit__(self, *args):
        self.close()

    def close(self):
        self.destroy_ef()
        if self._solver is not None:
            self._solver.deactivate()
        if self._solver_manager is not None:
            if isinstance(self._solver_manager,
                          pyomo.solvers.plugins.smanager.\
                          pyro.SolverManager_Pyro):
                if self.get_option("pyro_shutdown_workers"):
                      self._solver_manager.shutdown_workers()
            self._solver_manager.deactivate()
        self._solver_manager = None

        self._manager = None
        self.objective = undefined
        self.objective_sense = undefined
        self.gap = undefined
        self.termination_condition = undefined
        self.solver_status = undefined
        self.solution_status = undefined
        self.solver_results = undefined
        self.pyomo_solve_time = undefined
        self.solve_time = undefined

    def __init__(self, manager, *args, **kwds):
        import pyomo.solvers.plugins.smanager.pyro
        super(ExtensiveFormAlgorithm, self).__init__(*args, **kwds)

        # TODO: after PH moves over to the new code
        #if not isinstance(manager, ScenarioTreeManager):
        #    raise TypeError("ExtensiveFormAlgorithm requires an instance of the "
        #                    "ScenarioTreeManager interface as the "
        #                    "second argument")
        if not manager.initialized:
            raise ValueError("ExtensiveFormAlgorithm requires a scenario tree "
                             "manager that has been fully initialized")

        self._manager = manager
        self.instance = None
        self._solver_manager = None
        self._solver = None

        # The following attributes will be modified by the
        # solve() method. For users that are scripting, these
        # can be accessed after the solve() method returns.
        # They will be reset each time solve() is called.
        ############################################
        self.objective = undefined
        self.gap = undefined
        self.termination_condition = undefined
        self.solver_status = undefined
        self.solution_status = undefined
        self.solver_results = undefined
        self.pyomo_solve_time = undefined
        self.solve_time = undefined
        ############################################

        self._solver = SolverFactory(self.get_option("solver"),
                                     solver_io=self.get_option("solver_io"))
        if isinstance(self._solver, UnknownSolver):
            raise ValueError("Failed to create solver of type="+
                             self.get_option("solver")+
                             " for use in extensive form solve")
        if len(self.get_option("solver_options")) > 0:
            if self.get_option("verbose"):
                print("Initializing ef solver with options="
                      +str(list(self.get_option("solver_options"))))
            self._solver.set_options("".join(self.get_option("solver_options")))
        if self.get_option("mipgap") is not None:
            if (self.get_option("mipgap") < 0.0) or \
               (self.get_option("mipgap") > 1.0):
                raise ValueError("Value of the mipgap parameter for the EF "
                                 "solve must be on the unit interval; "
                                 "value specified="+str(self.get_option("mipgap")))
            self._solver.options.mipgap = float(self.get_option("mipgap"))

        solver_manager_type = self.get_option("solver_manager")
        if solver_manager_type == "phpyro":
            print("*** WARNING ***: PHPyro is not a supported solver "
                  "manager type for the extensive-form solver. "
                  "Falling back to serial.")
            solver_manager_type = 'serial'

        self._solver_manager = SolverManagerFactory(
            solver_manager_type,
            host=self.get_option("pyro_host"),
            port=self.get_option("pyro_port"))
        if self._solver_manager is None:
            raise ValueError("Failed to create solver manager of type="
                             +self.get_option("solver")+
                             " for use in extensive form solve")

    def build_ef(self):
        self.destroy_ef()
        if self.get_option("verbose"):
            print("Creating extensive form instance")
        start_time = time.time()

        # then validate the associated parameters.
        generate_weighted_cvar = False
        cvar_weight = None
        risk_alpha = None
        if self.get_option("generate_weighted_cvar"):
            generate_weighted_cvar = True
            cvar_weight = self.get_option("cvar_weight")
            risk_alpha = self.get_option("risk_alpha")

        self.instance = create_ef_instance(
            self._manager.scenario_tree,
            verbose_output=self.get_option("verbose"),
            generate_weighted_cvar=generate_weighted_cvar,
            cvar_weight=cvar_weight,
            risk_alpha=risk_alpha,
            cc_indicator_var_name=self.get_option("cc_indicator_var"),
            cc_alpha=self.get_option("cc_alpha"))

        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to construct extensive form instance=%.2f seconds"
                  %(time.time() - start_time))

    def destroy_ef(self):
        if self.instance is not None:
            for scenario in self._manager.scenario_tree.scenarios:
                self.instance.del_component(scenario.name)
                scenario._instance_objective.activate()
        self.instance = None

    def write(self, filename):

        if self.instance is None:
            raise RuntimeError(
                "The extensive form instance has not been constructed."
                "Call the build_ef() method to construct it.")

        suf = os.path.splitext(filename)[1]
        if suf not in ['.nl','.lp','.mps']:
            if self._solver.problem_format() == ProblemFormat.cpxlp:
                filename += '.lp'
            elif self._solver.problem_format() == ProblemFormat.nl:
                filename += '.nl'
            elif self._solver.problem_format() == ProblemFormat.mps:
                filename += '.mps'
            else:
                raise ValueError("Could not determine output file format. "
                                 "No recognized ending suffix was provided "
                                 "and no format was indicated was by the "
                                 "--solver-io option.")

        start_time = time.time()
        if self.get_option("verbose"):
            print("Starting to write extensive form")

        smap_id = write_ef(self.instance,
                           filename,
                           self.get_option("symbolic_solver_labels"))

        print("Extensive form written to file="+filename)
        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to write output file=%.2f seconds"
                  % (time.time() - start_time))

        return filename, smap_id

    def solve(self,
              check_status=True,
              exception_on_failure=True,
              io_options=None):

        if self.instance is None:
            raise RuntimeError(
                "The extensive form instance has not been constructed."
                "Call the build_ef() method to construct it.")

        start_time = time.time()
        if self.get_option("verbose"):
            print("Queuing extensive form solve")

        self.objective = undefined
        self.gap = undefined
        self.bound = undefined
        self.pyomo_solve_time = undefined
        self.solve_time = undefined
        self.termination_condition = undefined
        self.solver_status = undefined
        self.solution_status = undefined
        self.solver_results = undefined

        if isinstance(self._solver, PersistentSolver):
            self._solver.compile_instance(
                self.instance,
                symbolic_solver_labels=self.get_option("symbolic_solver_labels"))

        solve_kwds = {}
        solve_kwds['load_solutions'] = False
        if self.get_option("keep_solver_files"):
            solve_kwds['keepfiles'] = True
        if self.get_option("symbolic_solver_labels"):
            solve_kwds['symbolic_solver_labels'] = True
        if self.get_option("output_solver_log"):
            solve_kwds['tee'] = True

        if io_options is not None:
            solve_kwds.update(io_options)

        self.objective_sense = \
            find_active_objective(self.instance).sense

        if (not self.get_option("disable_warmstart")) and \
           (self._solver.warm_start_capable()):
            action_handle = self._solver_manager.queue(self.instance,
                                                       opt=self._solver,
                                                       warmstart=True,
                                                       **solve_kwds)
        else:
            action_handle = self._solver_manager.queue(self.instance,
                                                       opt=self._solver,
                                                       **solve_kwds)

        if self.get_option("verbose"):
            print("Waiting for extensive form solve")
        results = self._solver_manager.wait_for(action_handle)

        if self.get_option("verbose"):
            print("Done with extensive form solve - loading results")

        if self.get_option("output_solver_results"):
            print("Results for ef:")
            results.write(num=1)

        self.solver_results = results
        if hasattr(results.solver,"user_time") and \
           (not isinstance(results.solver.user_time,
                           UndefinedData)) and \
           (results.solver.user_time is not None):
            # the solve time might be a string, or might
            # not be - we eventually would like more
            # consistency on this front from the solver
            # plugins.
            self.solve_time = \
                float(results.solver.user_time)
        elif hasattr(results.solver,"time"):
            self.solve_time = \
                float(results.solver.time)
        else:
            self.solve_time = undefined

        if hasattr(results,"pyomo_solve_time"):
            self.pyomo_solve_time = \
                results.pyomo_solve_time
        else:
            self.pyomo_solve_times = undefined

        self.termination_condition = \
            results.solver.termination_condition
        self.solver_status = \
            results.solver.status

        if len(results.solution) > 0:
            assert len(results.solution) == 1

            results_sm = results._smap
            self.instance.solutions.load_from(results)

            solution0 = results.solution(0)
            if hasattr(solution0, "gap") and \
               (solution0.gap is not None):
                self.gap = solution0.gap
            else:
                self.gap = undefined

            self.solution_status = solution0.status

            if self.get_option("verbose"):
                print("Storing solution in scenario tree")

            for scenario in self._manager.scenario_tree.scenarios:
                scenario.update_solution_from_instance()
            self._manager.scenario_tree.snapshotSolutionFromScenarios()
            self.objective = self._manager.scenario_tree.\
                             findRootNode().\
                             computeExpectedNodeCost()
            if self.gap is not undefined:
                if self.objective_sense == pyomo.core.base.minimize:
                    self.bound = self.objective - self.gap
                else:
                    self.bound = self.objective + self.gap

        else:

            self.objective = undefined
            self.gap = undefined
            self.bound = undefined
            self.solution_status = undefined

        failure = False

        if check_status:
            if not ((self.solution_status == SolutionStatus.optimal) or \
                    (self.solution_status == SolutionStatus.feasible)):
                failure = True
                if self.get_option("verbose") or \
                   exception_on_failure:
                    msg = ("EF solve failed solution status check:\n"
                           "Solver Status: %s\n"
                           "Termination Condition: %s\n"
                           "Solution Status: %s\n"
                           % (self.solver_status,
                              self.termination_condition,
                              self.solution_status))
                    if self.get_option("verbose"):
                        print(msg)
                    if exception_on_failure:
                        raise RuntimeError(msg)
        else:
            if self.get_option("verbose"):
                print("EF solve completed. Skipping status check.")

        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to solve and load results for the "
                  "extensive form=%.2f seconds"
                  % (time.time()-start_time))

        return failure
Пример #11
0
    def __init__(self, manager, *args, **kwds):
        import pyomo.solvers.plugins.smanager.pyro
        super(ExtensiveFormAlgorithm, self).__init__(*args, **kwds)

        # TODO: after PH moves over to the new code
        #if not isinstance(manager, ScenarioTreeManager):
        #    raise TypeError("ExtensiveFormAlgorithm requires an instance of the "
        #                    "ScenarioTreeManager interface as the "
        #                    "second argument")
        if not manager.initialized:
            raise ValueError("ExtensiveFormAlgorithm requires a scenario tree "
                             "manager that has been fully initialized")

        self._manager = manager
        self.instance = None
        self._solver_manager = None
        self._solver = None

        # The following attributes will be modified by the
        # solve() method. For users that are scripting, these
        # can be accessed after the solve() method returns.
        # They will be reset each time solve() is called.
        ############################################
        self.objective = undefined
        self.gap = undefined
        self.termination_condition = undefined
        self.solver_status = undefined
        self.solution_status = undefined
        self.solver_results = undefined
        self.pyomo_solve_time = undefined
        self.solve_time = undefined
        ############################################

        self._solver = SolverFactory(self.get_option("solver"),
                                     solver_io=self.get_option("solver_io"))
        if isinstance(self._solver, UnknownSolver):
            raise ValueError("Failed to create solver of type="+
                             self.get_option("solver")+
                             " for use in extensive form solve")
        if len(self.get_option("solver_options")) > 0:
            if self.get_option("verbose"):
                print("Initializing ef solver with options="
                      +str(list(self.get_option("solver_options"))))
            self._solver.set_options("".join(self.get_option("solver_options")))
        if self.get_option("mipgap") is not None:
            if (self.get_option("mipgap") < 0.0) or \
               (self.get_option("mipgap") > 1.0):
                raise ValueError("Value of the mipgap parameter for the EF "
                                 "solve must be on the unit interval; "
                                 "value specified="+str(self.get_option("mipgap")))
            self._solver.options.mipgap = float(self.get_option("mipgap"))

        solver_manager_type = self.get_option("solver_manager")
        if solver_manager_type == "phpyro":
            print("*** WARNING ***: PHPyro is not a supported solver "
                  "manager type for the extensive-form solver. "
                  "Falling back to serial.")
            solver_manager_type = 'serial'

        self._solver_manager = SolverManagerFactory(
            solver_manager_type,
            host=self.get_option("pyro_host"),
            port=self.get_option("pyro_port"))
        if self._solver_manager is None:
            raise ValueError("Failed to create solver manager of type="
                             +self.get_option("solver")+
                             " for use in extensive form solve")
Пример #12
0
    def __init__(self, *args, **kwds):
        if self.__class__ is _ScenarioTreeManagerSolverWorker:
            raise NotImplementedError(
                "%s is an abstract class for subclassing" % self.__class__)

        super(_ScenarioTreeManagerSolverWorker, self).__init__(*args, **kwds)
        # 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 self.manager is not None

        # solver related objects
        self._scenario_solvers = {}
        self._bundle_solvers = {}
        self._preprocessor = None
        self._solver_manager = None

        # there are situations in which it is valuable to snapshot /
        # store the solutions associated with the scenario
        # instances. for example, when one wants to use a warm-start
        # from a particular iteration solve, following a modification
        # and re-solve of the problem instances in a user-defined
        # callback. the following nested dictionary is intended to
        # serve that purpose. The nesting is dependent on whether
        # bundling and or phpyro is in use
        self._cached_solutions = {}
        self._cached_scenariotree_solutions = {}

        #
        # initialize the preprocessor
        #
        self._preprocessor = None
        if not self.get_option("disable_advanced_preprocessing"):
            self._preprocessor = ScenarioTreePreprocessor(self._options,
                                                          options_prefix=self._options_prefix)
        assert self._manager.preprocessor is None
        self._manager.preprocessor = self._preprocessor

        #
        # initialize the solver manager
        #
        self._solver_manager = SolverManagerFactory(
            self.get_option("solver_manager"),
            host=self.get_option('solver_manager_pyro_host'),
            port=self.get_option('solver_manager_pyro_port'))
        for scenario in self.manager.scenario_tree._scenarios:
            assert scenario._instance is not None
            solver = self._scenario_solvers[scenario.name] = \
                SolverFactory(self.get_option("solver"),
                              solver_io=self.get_option("solver_io"))
            if isinstance(solver, PersistentSolver) and \
               self.get_option("disable_advanced_preprocessing"):
                raise ValueError("Advanced preprocessing can not be disabled "
                                 "when persistent solvers are used")
            if self._preprocessor is not None:
                self._preprocessor.add_scenario(scenario,
                                                scenario._instance,
                                                solver)
        for bundle in self.manager.scenario_tree._scenario_bundles:
            solver = self._bundle_solvers[bundle.name] = \
                SolverFactory(self.get_option("solver"),
                              solver_io=self.get_option("solver_io"))
            if isinstance(solver, PersistentSolver) and \
               self.get_option("disable_advanced_preprocessing"):
                raise ValueError("Advanced preprocessing can not be disabled "
                                 "when persistent solvers are used")
            bundle_instance = \
                self.manager._bundle_binding_instance_map[bundle.name]
            if self._preprocessor is not None:
                self._preprocessor.add_bundle(bundle,
                                              bundle_instance,
                                              solver)
def EFAlgorithmBuilder(options, scenario_tree):

    solution_writer_plugins = ExtensionPoint(ISolutionWriterExtension)
    for plugin in solution_writer_plugins:
        plugin.disable()

    solution_plugins = []
    if len(options.solution_writer) > 0:
        for this_extension in options.solution_writer:
            if this_extension in sys.modules:
                print("User-defined EF solution writer module="
                      +this_extension+" already imported - skipping")
            else:
                print("Trying to import user-defined EF "
                      "solution writer module="+this_extension)
                # make sure "." is in the PATH.
                original_path = list(sys.path)
                sys.path.insert(0,'.')
                pyutilib.misc.import_file(this_extension)
                print("Module successfully loaded")
                sys.path[:] = original_path # restore to what it was

            # now that we're sure the module is loaded, re-enable this
            # specific plugin.  recall that all plugins are disabled
            # by default in phinit.py, for various reasons. if we want
            # them to be picked up, we need to enable them explicitly.
            import inspect
            module_to_find = this_extension
            if module_to_find.rfind(".py"):
                module_to_find = module_to_find.rstrip(".py")
            if module_to_find.find("/") != -1:
                module_to_find = module_to_find.split("/")[-1]

            for name, obj in inspect.getmembers(sys.modules[module_to_find], inspect.isclass):
                import pyomo.util
                # the second condition gets around goofyness related to issubclass returning
                # True when the obj is the same as the test class.
                if issubclass(obj, pyomo.util.plugin.SingletonPlugin) and name != "SingletonPlugin":
                    for plugin in solution_writer_plugins(all=True):
                        if isinstance(plugin, obj):
                            plugin.enable()
                            solution_plugins.append(plugin)

    ef_solver = SolverFactory(options.solver_type,
                              solver_io=options.solver_io)
    if isinstance(ef_solver, UnknownSolver):
        raise ValueError("Failed to create solver of type="+
                         options.solver_type+
                         " for use in extensive form solve")
    if len(options.solver_options) > 0:
        print("Initializing ef solver with options="
              +str(options.solver_options))
        ef_solver.set_options("".join(options.solver_options))
    if options.mipgap is not None:
        if (options.mipgap < 0.0) or (options.mipgap > 1.0):
            raise ValueError("Value of the mipgap parameter for the EF "
                             "solve must be on the unit interval; "
                             "value specified="+str(options.mipgap))
        ef_solver.options.mipgap = float(options.mipgap)

    ef_solver_manager = SolverManagerFactory(options.solver_manager_type,
                                             host=options.pyro_host,
                                             port=options.pyro_port)
    if ef_solver_manager is None:
        raise ValueError("Failed to create solver manager of type="
                         +options.solver_type+
                         " for use in extensive form solve")

    binding_instance = CreateExtensiveFormInstance(options, scenario_tree)

    ef = ExtensiveFormAlgorithm(options,
                                binding_instance,
                                scenario_tree,
                                ef_solver_manager,
                                ef_solver,
                                solution_plugins=solution_plugins)

    return ef
Пример #14
0
Файл: ef.py Проект: Pyomo/pyomo
class ExtensiveFormAlgorithm(PySPConfiguredObject):

    @classmethod
    def _declare_options(cls, options=None):
        if options is None:
            options = PySPConfigBlock()

        safe_declare_unique_option(
            options,
            "cvar_weight",
            PySPConfigValue(
                1.0,
                domain=_domain_nonnegative,
                description=(
                    "The weight associated with the CVaR term in "
                    "the risk-weighted objective "
                    "formulation. If the weight is 0, then "
                    "*only* a non-weighted CVaR cost will appear "
                    "in the EF objective - the expected cost "
                    "component will be dropped. Default is 1.0."
                ),
                doc=None,
                visibility=0),
            ap_group=_ef_group_label)
        safe_declare_unique_option(
            options,
            "generate_weighted_cvar",
            PySPConfigValue(
                False,
                domain=bool,
                description=(
                    "Add a weighted CVaR term to the "
                    "primary objective. Default is False."
                ),
                doc=None,
                visibility=0),
            ap_group=_ef_group_label)
        safe_declare_unique_option(
            options,
            "risk_alpha",
            PySPConfigValue(
                0.95,
                domain=_domain_unit_interval,
                description=(
                    "The probability threshold associated with "
                    "CVaR (or any future) risk-oriented "
                    "performance metrics. Default is 0.95."
                ),
                doc=None,
                visibility=0),
            ap_group=_ef_group_label)
        safe_declare_unique_option(
            options,
            "cc_alpha",
            PySPConfigValue(
                0.0,
                domain=_domain_unit_interval,
                description=(
                    "The probability threshold associated with a "
                    "chance constraint. The RHS will be one "
                    "minus this value. Default is 0."
                ),
                doc=None,
                visibility=0),
            ap_group=_ef_group_label)
        safe_declare_unique_option(
            options,
            "cc_indicator_var",
            PySPConfigValue(
                None,
                domain=_domain_must_be_str,
                description=(
                    "The name of the binary variable to be used "
                    "to construct a chance constraint. Default "
                    "is None, which indicates no chance "
                    "constraint."
                ),
                doc=None,
                visibility=0),
            ap_group=_ef_group_label)
        safe_declare_common_option(options,
                                   "solver")
        safe_declare_common_option(options,
                                   "solver_io")
        safe_declare_common_option(options,
                                   "solver_manager")
        safe_declare_common_option(options,
                                   "solver_options")
        safe_declare_common_option(options,
                                   "disable_warmstart")
        safe_declare_common_option(options,
                                   "solver_manager_pyro_host")
        safe_declare_common_option(options,
                                   "solver_manager_pyro_port")
        safe_declare_common_option(options,
                                   "solver_manager_pyro_shutdown")
        safe_declare_common_option(options,
                                   "verbose",
                                   ap_group=_ef_group_label)
        safe_declare_common_option(options,
                                   "output_times",
                                   ap_group=_ef_group_label)
        safe_declare_common_option(options,
                                   "output_solver_results",
                                   ap_group=_ef_group_label)

        return options

    def __enter__(self):
        return self

    def __exit__(self, *args):
        self.close()

    def close(self):
        self.destroy_ef()
        if self._solver_manager is not None:
            if isinstance(self._solver_manager,
                          pyomo.solvers.plugins.smanager.\
                          pyro.SolverManager_Pyro):
                if self.get_option("pyro_shutdown_workers"):
                      self._solver_manager.shutdown_workers()
        self._solver_manager = None
        self._manager = None

    def __init__(self, manager, *args, **kwds):
        import pyomo.solvers.plugins.smanager.pyro
        super(ExtensiveFormAlgorithm, self).__init__(*args, **kwds)

        # TODO: after PH moves over to the new code
        #if not isinstance(manager, ScenarioTreeManager):
        #    raise TypeError("ExtensiveFormAlgorithm requires an instance of the "
        #                    "ScenarioTreeManager interface as the "
        #                    "second argument")
        if not manager.initialized:
            raise ValueError("ExtensiveFormAlgorithm requires a scenario tree "
                             "manager that has been fully initialized")

        self._manager = manager
        self.instance = None
        self._solver_manager = None
        self._solver = None

        # The following attributes will be modified by the
        # solve() method. For users that are scripting, these
        # can be accessed after the solve() method returns.
        # They will be reset each time solve() is called.
        ############################################
        self.objective = None
        self.gap = None
        self.termination_condition = None
        self.termination_message = None
        self.solver_status = None
        self.solution_status = None
        self.solver_results = None
        self.time = None
        self.pyomo_time = None
        ############################################

        # apparently the SolverFactory does not have sane
        # behavior when the solver name is None
        if self.get_option("solver") is None:
            raise ValueError("The 'solver' option can not be None")
        self._solver = SolverFactory(self.get_option("solver"),
                                     solver_io=self.get_option("solver_io"))
        if isinstance(self._solver, UnknownSolver):
            raise ValueError("Failed to create solver of type="+
                             self.get_option("solver")+
                             " for use in extensive form solve")

        solver_manager_type = self.get_option("solver_manager")
        if solver_manager_type == "phpyro":
            print("*** WARNING ***: PHPyro is not a supported solver "
                  "manager type for the extensive-form solver. "
                  "Falling back to serial.")
            solver_manager_type = 'serial'

        self._solver_manager = SolverManagerFactory(
            solver_manager_type,
            host=self.get_option("solver_manager_pyro_host"),
            port=self.get_option("solver_manager_pyro_port"))
        if self._solver_manager is None:
            raise ValueError("Failed to create solver manager of type="
                             +self.get_option("solver")+
                             " for use in extensive form solve")

    def build_ef(self):
        self.destroy_ef()
        if self.get_option("verbose"):
            print("Creating extensive form instance")
        start_time = time.time()

        # then validate the associated parameters.
        generate_weighted_cvar = False
        cvar_weight = None
        risk_alpha = None
        if self.get_option("generate_weighted_cvar"):
            generate_weighted_cvar = True
            cvar_weight = self.get_option("cvar_weight")
            risk_alpha = self.get_option("risk_alpha")

        self.instance = create_ef_instance(
            self._manager.scenario_tree,
            verbose_output=self.get_option("verbose"),
            generate_weighted_cvar=generate_weighted_cvar,
            cvar_weight=cvar_weight,
            risk_alpha=risk_alpha,
            cc_indicator_var_name=self.get_option("cc_indicator_var"),
            cc_alpha=self.get_option("cc_alpha"))

        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to construct extensive form instance=%.2f seconds"
                  %(time.time() - start_time))

    def destroy_ef(self):
        if self.instance is not None:
            for scenario in self._manager.scenario_tree.scenarios:
                self.instance.del_component(scenario.name)
                scenario._instance_objective.activate()
        self.instance = None

    def write(self, filename):

        if self.instance is None:
            raise RuntimeError(
                "The extensive form instance has not been constructed."
                "Call the build_ef() method to construct it.")

        suf = os.path.splitext(filename)[1]
        if suf not in ['.nl','.lp','.mps']:
            if self._solver.problem_format() == ProblemFormat.cpxlp:
                filename += '.lp'
            elif self._solver.problem_format() == ProblemFormat.nl:
                filename += '.nl'
            elif self._solver.problem_format() == ProblemFormat.mps:
                filename += '.mps'
            else:
                raise ValueError("Could not determine output file format. "
                                 "No recognized ending suffix was provided "
                                 "and no format was indicated was by the "
                                 "--solver-io option.")

        start_time = time.time()
        print("Writing extensive form to file="+filename)
        smap_id = write_ef(self.instance,
                           filename,
                           self.get_option("symbolic_solver_labels"))

        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to write output file=%.2f seconds"
                  % (time.time() - start_time))

        return filename, smap_id

    def solve(self,
              check_status=True,
              exception_on_failure=True,
              output_solver_log=False,
              symbolic_solver_labels=False,
              keep_solver_files=False,
              io_options=None):
        # TODO: Does this import need to be delayed because
        #       it is in a plugins subdirectory
        from pyomo.solvers.plugins.solvers.persistent_solver import \
            PersistentSolver

        if self.instance is None:
            raise RuntimeError(
                "The extensive form instance has not been constructed."
                "Call the build_ef() method to construct it.")

        start_time = time.time()
        if self.get_option("verbose"):
            print("Queuing extensive form solve")

        self.objective = None
        self.gap = None
        self.bound = None
        self.termination_condition = None
        self.termination_message = None
        self.solver_status = None
        self.solution_status = None
        self.solver_results = None
        self.time = None
        self.pyomo_time = None

        if isinstance(self._solver, PersistentSolver):
            self._solver.compile_instance(
                self.instance,
                symbolic_solver_labels=symbolic_solver_labels)

        solve_kwds = {}
        solve_kwds['load_solutions'] = False
        if keep_solver_files:
            solve_kwds['keepfiles'] = True
        if symbolic_solver_labels:
            solve_kwds['symbolic_solver_labels'] = True
        if output_solver_log:
            solve_kwds['tee'] = True

        solver_options = self.get_option("solver_options")
        if len(solver_options) > 0:
            if type(solver_options) is tuple:
                solve_kwds["options"] = {}
                for name_val in solver_options:
                    assert "=" in name_val
                    name, val = name_val.split("=")
                    solve_kwds["options"][name.strip()] = val.strip()
            else:
                solve_kwds["options"] = solver_options

        if io_options is not None:
            solve_kwds.update(io_options)

        self.objective_sense = \
            find_active_objective(self.instance).sense

        if (not self.get_option("disable_warmstart")) and \
           (self._solver.warm_start_capable()):
            action_handle = self._solver_manager.queue(self.instance,
                                                       opt=self._solver,
                                                       warmstart=True,
                                                       **solve_kwds)
        else:
            action_handle = self._solver_manager.queue(self.instance,
                                                       opt=self._solver,
                                                       **solve_kwds)

        if self.get_option("verbose"):
            print("Waiting for extensive form solve")
        results = self._solver_manager.wait_for(action_handle)

        if self.get_option("verbose"):
            print("Done with extensive form solve - loading results")

        if self.get_option("output_solver_results"):
            print("Results for ef:")
            results.write(num=1)

        self.solver_results = results
        if hasattr(results.solver,"user_time") and \
           (not isinstance(results.solver.user_time,
                           UndefinedData)) and \
           (results.solver.user_time is not None):
            # the solve time might be a string, or might
            # not be - we eventually would like more
            # consistency on this front from the solver
            # plugins.
            self.time = \
                float(results.solver.user_time)
        elif hasattr(results.solver,"time"):
            self.time = \
                float(results.solver.time)
        else:
            self.time = None

        if hasattr(results,"pyomo_solve_time"):
            self.pyomo_time = \
                results.pyomo_solve_time
        else:
            self.pyomo_time = None

        self.termination_condition = \
            results.solver.termination_condition
        self.termination_message = None
        if hasattr(results.solver,"termination_message"):
            self.termination_message = results.solver.termination_message
        elif hasattr(results.solver,"message"):
            self.termination_message = results.solver.message
        self.solver_status = \
            results.solver.status

        if len(results.solution) > 0:
            assert len(results.solution) == 1

            results_sm = results._smap
            self.instance.solutions.load_from(results)

            solution0 = results.solution(0)
            if hasattr(solution0, "gap") and \
               (solution0.gap is not None) and \
               (not isinstance(solution0.gap,
                               UndefinedData)):
                self.gap = float(solution0.gap)
            else:
                self.gap = None

            self.solution_status = solution0.status

            if self.get_option("verbose"):
                print("Storing solution in scenario tree")

            for scenario in self._manager.scenario_tree.scenarios:
                scenario.update_solution_from_instance()
            self._manager.scenario_tree.snapshotSolutionFromScenarios()
            self.objective = self._manager.scenario_tree.\
                             findRootNode().\
                             computeExpectedNodeCost()
            if self.gap is not None:
                if self.objective_sense == pyomo.core.base.minimize:
                    self.bound = self.objective - self.gap
                else:
                    self.bound = self.objective + self.gap

        else:

            self.objective = None
            self.gap = None
            self.bound = None
            self.solution_status = None

        failure = False

        if check_status:
            if not ((self.solution_status == SolutionStatus.optimal) or \
                    (self.solution_status == SolutionStatus.feasible)):
                failure = True
                if self.get_option("verbose") or \
                   exception_on_failure:
                    msg = ("EF solve failed solution status check:\n"
                           "Solver Status: %s\n"
                           "Termination Condition: %s\n"
                           "Solution Status: %s\n"
                           % (self.solver_status,
                              self.termination_condition,
                              self.solution_status))
                    if self.get_option("verbose"):
                        print(msg)
                    if exception_on_failure:
                        raise RuntimeError(msg)
        else:
            if self.get_option("verbose"):
                print("EF solve completed. Skipping status check.")

        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to solve and load results for the "
                  "extensive form=%.2f seconds"
                  % (time.time()-start_time))

        return failure
Пример #15
0
class _ScenarioTreeManagerSolverWorker(ScenarioTreeManagerSolver,
                                       PySPConfiguredObject):

    @classmethod
    def _declare_options(cls, options=None):
        if options is None:
            options = PySPConfigBlock()

        # options for controlling the solver manager
        # (not the scenario tree manager)
        safe_declare_common_option(options,
                                   "solver_manager_pyro_host")
        safe_declare_common_option(options,
                                   "solver_manager_pyro_port")
        safe_declare_common_option(options,
                                   "solver_manager_pyro_shutdown")

        ScenarioTreePreprocessor._declare_options(options)

        return options

    @property
    def preprocessor(self):
        return self._preprocessor

    def __init__(self, *args, **kwds):
        if self.__class__ is _ScenarioTreeManagerSolverWorker:
            raise NotImplementedError(
                "%s is an abstract class for subclassing" % self.__class__)

        super(_ScenarioTreeManagerSolverWorker, self).__init__(*args, **kwds)
        # 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 self.manager is not None

        # solver related objects
        self._scenario_solvers = {}
        self._bundle_solvers = {}
        self._preprocessor = None
        self._solver_manager = None

        # there are situations in which it is valuable to snapshot /
        # store the solutions associated with the scenario
        # instances. for example, when one wants to use a warm-start
        # from a particular iteration solve, following a modification
        # and re-solve of the problem instances in a user-defined
        # callback. the following nested dictionary is intended to
        # serve that purpose. The nesting is dependent on whether
        # bundling and or phpyro is in use
        self._cached_solutions = {}
        self._cached_scenariotree_solutions = {}

        #
        # initialize the preprocessor
        #
        self._preprocessor = None
        if not self.get_option("disable_advanced_preprocessing"):
            self._preprocessor = ScenarioTreePreprocessor(self._options,
                                                          options_prefix=self._options_prefix)
        assert self._manager.preprocessor is None
        self._manager.preprocessor = self._preprocessor

        #
        # initialize the solver manager
        #
        self._solver_manager = SolverManagerFactory(
            self.get_option("solver_manager"),
            host=self.get_option('solver_manager_pyro_host'),
            port=self.get_option('solver_manager_pyro_port'))
        for scenario in self.manager.scenario_tree._scenarios:
            assert scenario._instance is not None
            solver = self._scenario_solvers[scenario.name] = \
                SolverFactory(self.get_option("solver"),
                              solver_io=self.get_option("solver_io"))
            if isinstance(solver, PersistentSolver) and \
               self.get_option("disable_advanced_preprocessing"):
                raise ValueError("Advanced preprocessing can not be disabled "
                                 "when persistent solvers are used")
            if self._preprocessor is not None:
                self._preprocessor.add_scenario(scenario,
                                                scenario._instance,
                                                solver)
        for bundle in self.manager.scenario_tree._scenario_bundles:
            solver = self._bundle_solvers[bundle.name] = \
                SolverFactory(self.get_option("solver"),
                              solver_io=self.get_option("solver_io"))
            if isinstance(solver, PersistentSolver) and \
               self.get_option("disable_advanced_preprocessing"):
                raise ValueError("Advanced preprocessing can not be disabled "
                                 "when persistent solvers are used")
            bundle_instance = \
                self.manager._bundle_binding_instance_map[bundle.name]
            if self._preprocessor is not None:
                self._preprocessor.add_bundle(bundle,
                                              bundle_instance,
                                              solver)

    #
    # Override some methods for ScenarioTreeManager that
    # were implemented by _ScenarioTreeManagerWorker:
    #

    def _close_impl(self):
        if (self._manager is not None) and \
           (self._manager.preprocessor is not None):
            assert self.preprocessor is self._manager.preprocessor
            for bundle in self.manager.scenario_tree._scenario_bundles:
                self._preprocessor.remove_bundle(bundle)
            for scenario in self.manager.scenario_tree._scenarios:
                assert scenario._instance is not None
                self._preprocessor.remove_scenario(scenario)
            self._manager.preprocessor = None
            self._preprocessor = None
        else:
            assert self._preprocessor is None

        if self._solver_manager is not None:
            self._solver_manager.deactivate()
            self._solver_manager = None
            if self.get_option("solver_manager_pyro_shutdown"):
                print("Shutting down Pyro components for solver manager.")
                shutdown_pyro_components(
                    host=self.get_option("solver_manager_pyro_host"),
                    port=self.get_option("solver_manager_pyro_port"),
                    num_retries=0,
                    caller_name=self.__class__.__name__)
        for solver in self._scenario_solvers.values():
            solver.deactivate()
        self._scenario_solvers = {}
        for solver in self._bundle_solvers.values():
            solver.deactivate()
        self._bundle_solvers = {}
        self._preprocessor = None
        self._objective_sense = None

    #
    # Abstract methods for ScenarioTreeManagerSolver:
    #

    def _queue_object_solves(self,
                             object_type,
                             objects,
                             ephemeral_solver_options,
                             disable_warmstart):

        if self.get_option("verbose"):
            print("Queuing %s solves" % (object_type[:-1]))

        assert object_type in ('bundles', 'scenarios')

        solver_dict = None
        instance_dict = None
        modify_kwds_func = None
        if object_type == 'bundles':
            if objects is None:
                objects = self.manager.scenario_tree._scenario_bundle_map
            solver_dict = self._bundle_solvers
            instance_dict = self.manager._bundle_binding_instance_map
            for bundle_name in objects:
                for scenario_name in self.manager.scenario_tree.\
                    get_bundle(bundle_name).\
                       scenario_names:
                    self.manager.scenario_tree.get_scenario(scenario_name).\
                        _instance_objective.deactivate()
            if self.preprocessor is not None:
                self.preprocessor.preprocess_bundles(bundles=objects)
                modify_kwds_func = self.preprocessor.modify_bundle_solver_keywords
        else:
            if objects is None:
                objects = self.manager.scenario_tree._scenario_map
            solver_dict = self._scenario_solvers
            instance_dict = self.manager._instances
            if self.manager.scenario_tree.contains_bundles():
                for scenario_name in objects:
                    self.manager.scenario_tree.get_scenario(scenario_name).\
                        _instance_objective.activate()
            if self.preprocessor is not None:
                self.preprocessor.preprocess_scenarios(scenarios=objects)
                modify_kwds_func = self.preprocessor.modify_scenario_solver_keywords
        assert solver_dict is not None
        assert instance_dict is not None

        # setup common solve keywords
        common_kwds = {}
        common_kwds['tee'] = self.get_option("output_solver_log")
        common_kwds['keepfiles'] = self.get_option("keep_solver_files")
        common_kwds['symbolic_solver_labels'] = \
            self.get_option("symbolic_solver_labels")
        # we always manually load solutions, so we can
        # control error reporting and such
        common_kwds['load_solutions'] = False

        # Load solver options
        solver_options = {}
        if type(self.get_option("solver_options")) is tuple:
            solver_options.update(
                OptSolver._options_string_to_dict(
                    "".join(self.get_option("solver_options"))))
        else:
            solver_options.update(self.get_option("solver_options"))
        common_kwds['options'] = solver_options

        #
        # override "persistent" values that are included from this
        # classes registered options
        #
        if ephemeral_solver_options is not None:
            common_kwds['options'].update(ephemeral_solver_options)

        # maps action handles to subproblem names
        action_handle_data = {}
        for object_name in objects:

            if modify_kwds_func is not None:
                # be sure to modify a copy of the kwds
                solve_kwds = modify_kwds_func(object_name, dict(common_kwds))
            else:
                solve_kwds = common_kwds
            opt = solver_dict[object_name]
            instance = instance_dict[object_name]
            if (not self.get_option("disable_warmstart")) and \
               (not disable_warmstart) and \
               opt.warm_start_capable():
                new_action_handle = \
                    self._solver_manager.queue(instance,
                                               opt=opt,
                                               warmstart=True,
                                               **solve_kwds)
            else:
                new_action_handle = \
                    self._solver_manager.queue(instance,
                                               opt=opt,
                                               **solve_kwds)

            action_handle_data[new_action_handle] = object_name

        return self.manager.AsyncResult(
            self._solver_manager,
            action_handle_data=action_handle_data)
Пример #16
0
class ExtensiveFormAlgorithm(PySPConfiguredObject):

    _declared_options = \
        PySPConfigBlock("Options declared for the "
                        "ExtensiveFormAlgorithm class")

    safe_declare_unique_option(
        _declared_options,
        "cvar_weight",
        PySPConfigValue(
            1.0,
            domain=_domain_nonnegative,
            description=("The weight associated with the CVaR term in "
                         "the risk-weighted objective "
                         "formulation. If the weight is 0, then "
                         "*only* a non-weighted CVaR cost will appear "
                         "in the EF objective - the expected cost "
                         "component will be dropped. Default is 1.0."),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "generate_weighted_cvar",
        PySPConfigValue(False,
                        domain=bool,
                        description=("Add a weighted CVaR term to the "
                                     "primary objective. Default is False."),
                        doc=None,
                        visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "risk_alpha",
        PySPConfigValue(
            0.95,
            domain=_domain_unit_interval,
            description=("The probability threshold associated with "
                         "CVaR (or any future) risk-oriented "
                         "performance metrics. Default is 0.95."),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "cc_alpha",
        PySPConfigValue(
            0.0,
            domain=_domain_unit_interval,
            description=("The probability threshold associated with a "
                         "chance constraint. The RHS will be one "
                         "minus this value. Default is 0."),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "cc_indicator_var",
        PySPConfigValue(
            None,
            domain=_domain_must_be_str,
            description=("The name of the binary variable to be used "
                         "to construct a chance constraint. Default "
                         "is None, which indicates no chance "
                         "constraint."),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "mipgap",
        PySPConfigValue(None,
                        domain=_domain_unit_interval,
                        description=("Specifies the mipgap for the EF solve."),
                        doc=None,
                        visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "solver",
        PySPConfigValue(
            "cplex",
            domain=_domain_must_be_str,
            description=("Specifies the solver used to solve the "
                         "extensive form model. Default is cplex."),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "solver_io",
        PySPConfigValue(
            None,
            domain=_domain_must_be_str,
            description=("The type of IO used to execute the "
                         "solver. Different solvers support different "
                         "types of IO, but the following are common "
                         "options: lp - generate LP files, nl - "
                         "generate NL files, python - direct Python "
                         "interface, os - generate OSiL XML files."),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "solver_manager",
        PySPConfigValue('serial',
                        domain=_domain_must_be_str,
                        description=("The type of solver manager used to "
                                     "coordinate solves. Default is serial."),
                        doc=None,
                        visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "solver_options",
        PySPConfigValue((),
                        domain=_domain_tuple_of_str_or_dict,
                        description=("Persistent solver options used when "
                                     "solving the extensive form model. This "
                                     "option can be used multiple times from "
                                     "the command line to specify more than "
                                     "one solver option."),
                        doc=None,
                        visibility=0),
        ap_kwds={'action': 'append'},
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "disable_warmstart",
        PySPConfigValue(False,
                        domain=bool,
                        description=("Disable warm-start of EF solves. "
                                     "Default is False."),
                        doc=None,
                        visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "pyro_host",
        PySPConfigValue(None,
                        domain=_domain_must_be_str,
                        description=("The hostname to bind on when searching "
                                     "for a Pyro nameserver."),
                        doc=None,
                        visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "pyro_port",
        PySPConfigValue(None,
                        domain=_domain_nonnegative_integer,
                        description=("The port to bind on when searching for "
                                     "a Pyro nameserver."),
                        doc=None,
                        visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "pyro_shutdown",
        PySPConfigValue(
            False,
            domain=bool,
            description=(
                "Attempt to shut down all Pyro-related components "
                "associated with the Pyro name server used by any scenario "
                "tree manager or solver manager. Components to shutdown "
                "include the name server, dispatch server, and any "
                "scenariotreeserver or pyro_mip_server processes. Note "
                "that if Pyro4 is in use the nameserver will always "
                "ignore this request."),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_unique_option(
        _declared_options,
        "pyro_shutdown_workers",
        PySPConfigValue(
            False,
            domain=bool,
            description=(
                "Upon exit, send shutdown requests to all worker "
                "processes that were acquired through the dispatcher. "
                "This typically includes scenariotreeserver processes "
                "(used by the Pyro scenario tree manager) and pyro_mip_server "
                "processes (used by the Pyro solver manager). This leaves "
                "any dispatchers and namservers running as well as any "
                "processes registered with the dispather that were not "
                "acquired for work by this client."),
            doc=None,
            visibility=0),
        ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "symbolic_solver_labels",
                               ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "output_solver_log",
                               ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "verbose",
                               ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "output_times",
                               ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "keep_solver_files",
                               ap_group=_ef_group_label)
    safe_declare_common_option(_declared_options,
                               "output_solver_results",
                               ap_group=_ef_group_label)

    def __enter__(self):
        return self

    def __exit__(self, *args):
        self.close()

    def close(self):
        self.destroy_ef()
        if self._solver is not None:
            self._solver.deactivate()
        if self._solver_manager is not None:
            if isinstance(self._solver_manager,
                          pyomo.solvers.plugins.smanager.\
                          pyro.SolverManager_Pyro):
                if self.get_option("pyro_shutdown_workers"):
                    self._solver_manager.shutdown_workers()
            self._solver_manager.deactivate()
        self._solver_manager = None

        self._manager = None
        self.objective = undefined
        self.objective_sense = undefined
        self.gap = undefined
        self.termination_condition = undefined
        self.solver_status = undefined
        self.solution_status = undefined
        self.solver_results = undefined
        self.pyomo_solve_time = undefined
        self.solve_time = undefined

    def __init__(self, manager, *args, **kwds):
        import pyomo.solvers.plugins.smanager.pyro
        super(ExtensiveFormAlgorithm, self).__init__(*args, **kwds)

        # TODO: after PH moves over to the new code
        #if not isinstance(manager, ScenarioTreeManager):
        #    raise TypeError("ExtensiveFormAlgorithm requires an instance of the "
        #                    "ScenarioTreeManager interface as the "
        #                    "second argument")
        if not manager.initialized:
            raise ValueError("ExtensiveFormAlgorithm requires a scenario tree "
                             "manager that has been fully initialized")

        self._manager = manager
        self.instance = None
        self._solver_manager = None
        self._solver = None

        # The following attributes will be modified by the
        # solve() method. For users that are scripting, these
        # can be accessed after the solve() method returns.
        # They will be reset each time solve() is called.
        ############################################
        self.objective = undefined
        self.gap = undefined
        self.termination_condition = undefined
        self.solver_status = undefined
        self.solution_status = undefined
        self.solver_results = undefined
        self.pyomo_solve_time = undefined
        self.solve_time = undefined
        ############################################

        self._solver = SolverFactory(self.get_option("solver"),
                                     solver_io=self.get_option("solver_io"))
        if isinstance(self._solver, UnknownSolver):
            raise ValueError("Failed to create solver of type=" +
                             self.get_option("solver") +
                             " for use in extensive form solve")
        if len(self.get_option("solver_options")) > 0:
            if self.get_option("verbose"):
                print("Initializing ef solver with options=" +
                      str(list(self.get_option("solver_options"))))
            self._solver.set_options("".join(
                self.get_option("solver_options")))
        if self.get_option("mipgap") is not None:
            if (self.get_option("mipgap") < 0.0) or \
               (self.get_option("mipgap") > 1.0):
                raise ValueError("Value of the mipgap parameter for the EF "
                                 "solve must be on the unit interval; "
                                 "value specified=" +
                                 str(self.get_option("mipgap")))
            self._solver.options.mipgap = float(self.get_option("mipgap"))

        solver_manager_type = self.get_option("solver_manager")
        if solver_manager_type == "phpyro":
            print("*** WARNING ***: PHPyro is not a supported solver "
                  "manager type for the extensive-form solver. "
                  "Falling back to serial.")
            solver_manager_type = 'serial'

        self._solver_manager = SolverManagerFactory(
            solver_manager_type,
            host=self.get_option("pyro_host"),
            port=self.get_option("pyro_port"))
        if self._solver_manager is None:
            raise ValueError("Failed to create solver manager of type=" +
                             self.get_option("solver") +
                             " for use in extensive form solve")

    def build_ef(self):
        self.destroy_ef()
        if self.get_option("verbose"):
            print("Creating extensive form instance")
        start_time = time.time()

        # then validate the associated parameters.
        generate_weighted_cvar = False
        cvar_weight = None
        risk_alpha = None
        if self.get_option("generate_weighted_cvar"):
            generate_weighted_cvar = True
            cvar_weight = self.get_option("cvar_weight")
            risk_alpha = self.get_option("risk_alpha")

        self.instance = create_ef_instance(
            self._manager.scenario_tree,
            verbose_output=self.get_option("verbose"),
            generate_weighted_cvar=generate_weighted_cvar,
            cvar_weight=cvar_weight,
            risk_alpha=risk_alpha,
            cc_indicator_var_name=self.get_option("cc_indicator_var"),
            cc_alpha=self.get_option("cc_alpha"))

        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to construct extensive form instance=%.2f seconds" %
                  (time.time() - start_time))

    def destroy_ef(self):
        if self.instance is not None:
            for scenario in self._manager.scenario_tree.scenarios:
                self.instance.del_component(scenario.name)
                scenario._instance_objective.activate()
        self.instance = None

    def write(self, filename):

        if self.instance is None:
            raise RuntimeError(
                "The extensive form instance has not been constructed."
                "Call the build_ef() method to construct it.")

        suf = os.path.splitext(filename)[1]
        if suf not in ['.nl', '.lp', '.mps']:
            if self._solver.problem_format() == ProblemFormat.cpxlp:
                filename += '.lp'
            elif self._solver.problem_format() == ProblemFormat.nl:
                filename += '.nl'
            elif self._solver.problem_format() == ProblemFormat.mps:
                filename += '.mps'
            else:
                raise ValueError("Could not determine output file format. "
                                 "No recognized ending suffix was provided "
                                 "and no format was indicated was by the "
                                 "--solver-io option.")

        start_time = time.time()
        if self.get_option("verbose"):
            print("Starting to write extensive form")

        smap_id = write_ef(self.instance, filename,
                           self.get_option("symbolic_solver_labels"))

        print("Extensive form written to file=" + filename)
        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to write output file=%.2f seconds" %
                  (time.time() - start_time))

        return filename, smap_id

    def solve(self,
              check_status=True,
              exception_on_failure=True,
              io_options=None):

        if self.instance is None:
            raise RuntimeError(
                "The extensive form instance has not been constructed."
                "Call the build_ef() method to construct it.")

        start_time = time.time()
        if self.get_option("verbose"):
            print("Queuing extensive form solve")

        self.objective = undefined
        self.gap = undefined
        self.bound = undefined
        self.pyomo_solve_time = undefined
        self.solve_time = undefined
        self.termination_condition = undefined
        self.solver_status = undefined
        self.solution_status = undefined
        self.solver_results = undefined

        if isinstance(self._solver, PersistentSolver):
            self._solver.set_instance(self.instance,
                                      symbolic_solver_labels=self.get_option(
                                          "symbolic_solver_labels"))

        solve_kwds = {}
        solve_kwds['load_solutions'] = False
        if self.get_option("keep_solver_files"):
            solve_kwds['keepfiles'] = True
        if self.get_option("symbolic_solver_labels"):
            solve_kwds['symbolic_solver_labels'] = True
        if self.get_option("output_solver_log"):
            solve_kwds['tee'] = True

        if io_options is not None:
            solve_kwds.update(io_options)

        self.objective_sense = \
            find_active_objective(self.instance).sense

        if (not self.get_option("disable_warmstart")) and \
           (self._solver.warm_start_capable()):
            action_handle = self._solver_manager.queue(self.instance,
                                                       opt=self._solver,
                                                       warmstart=True,
                                                       **solve_kwds)
        else:
            action_handle = self._solver_manager.queue(self.instance,
                                                       opt=self._solver,
                                                       **solve_kwds)

        if self.get_option("verbose"):
            print("Waiting for extensive form solve")
        results = self._solver_manager.wait_for(action_handle)

        if self.get_option("verbose"):
            print("Done with extensive form solve - loading results")

        if self.get_option("output_solver_results"):
            print("Results for ef:")
            results.write(num=1)

        self.solver_results = results
        if hasattr(results.solver,"user_time") and \
           (not isinstance(results.solver.user_time,
                           UndefinedData)) and \
           (results.solver.user_time is not None):
            # the solve time might be a string, or might
            # not be - we eventually would like more
            # consistency on this front from the solver
            # plugins.
            self.solve_time = \
                float(results.solver.user_time)
        elif hasattr(results.solver, "time"):
            self.solve_time = \
                float(results.solver.time)
        else:
            self.solve_time = undefined

        if hasattr(results, "pyomo_solve_time"):
            self.pyomo_solve_time = \
                results.pyomo_solve_time
        else:
            self.pyomo_solve_times = undefined

        self.termination_condition = \
            results.solver.termination_condition
        self.solver_status = \
            results.solver.status

        if len(results.solution) > 0:
            assert len(results.solution) == 1

            results_sm = results._smap
            self.instance.solutions.load_from(results)

            solution0 = results.solution(0)
            if hasattr(solution0, "gap") and \
               (solution0.gap is not None):
                self.gap = solution0.gap
            else:
                self.gap = undefined

            self.solution_status = solution0.status

            if self.get_option("verbose"):
                print("Storing solution in scenario tree")

            for scenario in self._manager.scenario_tree.scenarios:
                scenario.update_solution_from_instance()
            self._manager.scenario_tree.snapshotSolutionFromScenarios()
            self.objective = self._manager.scenario_tree.\
                             findRootNode().\
                             computeExpectedNodeCost()
            if self.gap is not undefined:
                if self.objective_sense == pyomo.core.base.minimize:
                    self.bound = self.objective - self.gap
                else:
                    self.bound = self.objective + self.gap

        else:

            self.objective = undefined
            self.gap = undefined
            self.bound = undefined
            self.solution_status = undefined

        failure = False

        if check_status:
            if not ((self.solution_status == SolutionStatus.optimal) or \
                    (self.solution_status == SolutionStatus.feasible)):
                failure = True
                if self.get_option("verbose") or \
                   exception_on_failure:
                    msg = ("EF solve failed solution status check:\n"
                           "Solver Status: %s\n"
                           "Termination Condition: %s\n"
                           "Solution Status: %s\n" %
                           (self.solver_status, self.termination_condition,
                            self.solution_status))
                    if self.get_option("verbose"):
                        print(msg)
                    if exception_on_failure:
                        raise RuntimeError(msg)
        else:
            if self.get_option("verbose"):
                print("EF solve completed. Skipping status check.")

        if self.get_option("verbose") or self.get_option("output_times"):
            print("Time to solve and load results for the "
                  "extensive form=%.2f seconds" % (time.time() - start_time))

        return failure
Пример #17
0
def BenderAlgorithmBuilder(options, scenario_tree):

    import pyomo.environ
    import pyomo.solvers.plugins.smanager.phpyro
    import pyomo.solvers.plugins.smanager.pyro

    solution_writer_plugins = ExtensionPoint(ISolutionWriterExtension)
    for plugin in solution_writer_plugins:
        plugin.disable()

    solution_plugins = []
    if len(options.solution_writer) > 0:
        for this_extension in options.solution_writer:
            if this_extension in sys.modules:
                print("User-defined PH solution writer module=" +
                      this_extension + " already imported - skipping")
            else:
                print("Trying to import user-defined PH "
                      "solution writer module=" + this_extension)
                # make sure "." is in the PATH.
                original_path = list(sys.path)
                sys.path.insert(0, '.')
                import_file(this_extension)
                print("Module successfully loaded")
                sys.path[:] = original_path  # restore to what it was

            # now that we're sure the module is loaded, re-enable this
            # specific plugin.  recall that all plugins are disabled
            # by default in phinit.py, for various reasons. if we want
            # them to be picked up, we need to enable them explicitly.
            import inspect
            module_to_find = this_extension
            if module_to_find.rfind(".py"):
                module_to_find = module_to_find.rstrip(".py")
            if module_to_find.find("/") != -1:
                module_to_find = module_to_find.split("/")[-1]

            for name, obj in inspect.getmembers(sys.modules[module_to_find],
                                                inspect.isclass):
                import pyomo.common
                # the second condition gets around goofyness related
                # to issubclass returning True when the obj is the
                # same as the test class.
                if issubclass(obj, pyomo.common.plugin.SingletonPlugin
                              ) and name != "SingletonPlugin":
                    for plugin in solution_writer_plugins(all=True):
                        if isinstance(plugin, obj):
                            plugin.enable()
                            solution_plugins.append(plugin)

    #
    # if any of the ww extension configuration options are specified
    # without the ww extension itself being enabled, halt and warn the
    # user - this has led to confusion in the past, and will save user
    # support time.
    #
    if (len(options.ww_extension_cfgfile) > 0) and \
       (options.enable_ww_extensions is False):
        raise ValueError("A configuration file was specified "
                         "for the WW extension module, but the WW extensions "
                         "are not enabled!")

    if (len(options.ww_extension_suffixfile) > 0) and \
       (options.enable_ww_extensions is False):
        raise ValueError("A suffix file was specified for the WW "
                         "extension module, but the WW extensions are not "
                         "enabled!")

    if (len(options.ww_extension_annotationfile) > 0) and \
       (options.enable_ww_extensions is False):
        raise ValueError("A annotation file was specified for the "
                         "WW extension module, but the WW extensions are not "
                         "enabled!")

    #
    # disable all plugins up-front. then, enable them on an as-needed
    # basis later in this function. the reason that plugins should be
    # disabled is that they may have been programmatically enabled in
    # a previous run of PH, and we want to start from a clean slate.
    #
    ph_extension_point = ExtensionPoint(IPHExtension)

    for plugin in ph_extension_point:
        plugin.disable()

    ph_plugins = []
    #
    # deal with any plugins. ww extension comes first currently,
    # followed by an option user-defined plugin.  order only matters
    # if both are specified.
    #
    if options.enable_ww_extensions:

        import pyomo.pysp.plugins.wwphextension

        # explicitly enable the WW extension plugin - it may have been
        # previously loaded and/or enabled.
        ph_extension_point = ExtensionPoint(IPHExtension)

        for plugin in ph_extension_point(all=True):
            if isinstance(plugin,
                          pyomo.pysp.plugins.wwphextension.wwphextension):

                plugin.enable()
                ph_plugins.append(plugin)

                # there is no reset-style method for plugins in general,
                # or the ww ph extension in plugin in particular. if no
                # configuration or suffix filename is specified, set to
                # None so that remnants from the previous use of the
                # plugin aren't picked up.
                if len(options.ww_extension_cfgfile) > 0:
                    plugin._configuration_filename = options.ww_extension_cfgfile
                else:
                    plugin._configuration_filename = None
                if len(options.ww_extension_suffixfile) > 0:
                    plugin._suffix_filename = options.ww_extension_suffixfile
                else:
                    plugin._suffix_filename = None
                if len(options.ww_extension_annotationfile) > 0:
                    plugin._annotation_filename = options.ww_extension_annotationfile
                else:
                    plugin._annotation_filename = None

    if len(options.user_defined_extensions) > 0:
        for this_extension in options.user_defined_extensions:
            if this_extension in sys.modules:
                print("User-defined PH extension module=" + this_extension +
                      " already imported - skipping")
            else:
                print("Trying to import user-defined PH extension module=" +
                      this_extension)
                # make sure "." is in the PATH.
                original_path = list(sys.path)
                sys.path.insert(0, '.')
                import_file(this_extension)
                print("Module successfully loaded")
                # restore to what it was
                sys.path[:] = original_path

            # now that we're sure the module is loaded, re-enable this
            # specific plugin.  recall that all plugins are disabled
            # by default in phinit.py, for various reasons. if we want
            # them to be picked up, we need to enable them explicitly.
            import inspect
            module_to_find = this_extension
            if module_to_find.rfind(".py"):
                module_to_find = module_to_find.rstrip(".py")
            if module_to_find.find("/") != -1:
                module_to_find = module_to_find.split("/")[-1]

            for name, obj in inspect.getmembers(sys.modules[module_to_find],
                                                inspect.isclass):
                import pyomo.common
                # the second condition gets around goofyness related
                # to issubclass returning True when the obj is the
                # same as the test class.
                if issubclass(obj, pyomo.common.plugin.SingletonPlugin
                              ) and name != "SingletonPlugin":
                    ph_extension_point = ExtensionPoint(IPHExtension)
                    for plugin in ph_extension_point(all=True):
                        if isinstance(plugin, obj):
                            plugin.enable()
                            ph_plugins.append(plugin)

    ph = None
    solver_manager = None
    try:

        # construct the solver manager.
        if options.verbose:
            print("Constructing solver manager of type=" +
                  options.solver_manager_type)
        solver_manager = SolverManagerFactory(options.solver_manager_type,
                                              host=options.pyro_host,
                                              port=options.pyro_port)

        if solver_manager is None:
            raise ValueError("Failed to create solver manager of "
                             "type=" + options.solver_manager_type +
                             " specified in call to PH constructor")

        ph = ProgressiveHedging(options)

        if isinstance(
                solver_manager,
                pyomo.solvers.plugins.smanager.phpyro.SolverManager_PHPyro):

            if scenario_tree.contains_bundles():
                num_jobs = len(scenario_tree._scenario_bundles)
                if not _OLD_OUTPUT:
                    print("Bundle solver jobs available: " + str(num_jobs))
            else:
                num_jobs = len(scenario_tree._scenarios)
                if not _OLD_OUTPUT:
                    print("Scenario solver jobs available: " + str(num_jobs))

            servers_expected = options.phpyro_required_workers
            if (servers_expected is None):
                servers_expected = num_jobs

            timeout = options.phpyro_workers_timeout if \
                      (options.phpyro_required_workers is None) else \
                      None

            solver_manager.acquire_servers(servers_expected, timeout)

        ph.initialize(scenario_tree=scenario_tree,
                      solver_manager=solver_manager,
                      ph_plugins=ph_plugins,
                      solution_plugins=solution_plugins)

    except:

        if ph is not None:

            ph.release_components()

        if solver_manager is not None:

            if isinstance(
                    solver_manager, pyomo.solvers.plugins.smanager.phpyro.
                    SolverManager_PHPyro):
                solver_manager.release_servers(
                    shutdown=ph._shutdown_pyro_workers)
            elif isinstance(
                    solver_manager,
                    pyomo.solvers.plugins.smanager.pyro.SolverManager_Pyro):
                if ph._shutdown_pyro_workers:
                    solver_manager.shutdown_workers()

        print("Failed to initialize progressive hedging algorithm")
        raise

    return ph
Пример #18
0
def apply_optimizer(data, instance=None):
    """
    Perform optimization with a concrete instance

    Required:
        instance:   Problem instance.

    Returned:
        results:    Optimization results.
        opt:        Optimizer object.
    """
    #
    if not data.options.runtime.logging == 'quiet':
        sys.stdout.write('[%8.2f] Applying solver\n' % (time.time()-start_time))
        sys.stdout.flush()
    #
    #
    # Create Solver and Perform Optimization
    #
    solver = data.options.solvers[0].solver_name
    if solver is None:
        raise ValueError("Problem constructing solver:  no solver specified")

    if len(data.options.solvers[0].suffixes) > 0:
        for suffix_name in data.options.solvers[0].suffixes:
            if suffix_name[0] in ['"',"'"]:
                suffix_name = suffix[1:-1]
            # Don't redeclare the suffix if it already exists
            suffix = getattr(instance, suffix_name, None)
            if suffix is None:
                setattr(instance, suffix_name, Suffix(direction=Suffix.IMPORT))
            else:
                raise ValueError("Problem declaring solver suffix %s. A component "\
                                  "with that name already exists on model %s."
                                 % (suffix_name, instance.name))

    if getattr(data.options.solvers[0].options, 'timelimit', 0) == 0:
        data.options.solvers[0].options.timelimit = None
    #
    # Default results
    #
    results = None
    #
    # Figure out the type of solver manager
    #
    solver_mngr_name = None
    if data.options.solvers[0].manager is None:
        solver_mngr_name = 'serial'
    elif not data.options.solvers[0].manager in SolverManagerFactory.services():
        raise ValueError("Unknown solver manager %s"
                         % data.options.solvers[0].manager)
    else:
        solver_mngr_name = data.options.solvers[0].manager
    #
    # Create the solver manager
    #
    solver_mngr_kwds = {}
    if data.options.solvers[0].pyro_host is not None:
        solver_mngr_kwds['host'] = data.options.solvers[0].pyro_host
    if data.options.solvers[0].pyro_port is not None:
        solver_mngr_kwds['port'] = data.options.solvers[0].pyro_port
    with SolverManagerFactory(solver_mngr_name, **solver_mngr_kwds) as solver_mngr:
        if solver_mngr is None:
            msg = "Problem constructing solver manager '%s'"
            raise ValueError(msg % str(data.options.solvers[0].manager))
        #
        # Setup keywords for the solve
        #
        keywords = {}
        if (data.options.runtime.keep_files or \
            data.options.postsolve.print_logfile):
            keywords['keepfiles'] = True
        if data.options.model.symbolic_solver_labels:
            keywords['symbolic_solver_labels'] = True
        if data.options.model.file_determinism != 1:
            keywords['file_determinism'] = data.options.model.file_determinism
        keywords['tee'] = data.options.runtime.stream_output
        keywords['timelimit'] = getattr(data.options.solvers[0].options, 'timelimit', 0)
        #
        # Call the solver
        #
        if solver_mngr_name == 'serial':
            #
            # If we're running locally, then we create the optimizer and pass it into the 
            # solver manager.
            #
            with SolverFactory(solver, solver_io=data.options.solvers[0].io_format) as opt:
                if opt is None:
                    raise ValueError("Problem constructing solver `%s`" % str(solver))

                from pyomo.core.base.plugin import registered_callback
                for name in registered_callback:
                    opt.set_callback(name, registered_callback[name])

                if len(data.options.solvers[0].options) > 0:
                    opt.set_options(data.options.solvers[0].options)
                    #opt.set_options(" ".join("%s=%s" % (key, value)
                    #                         for key, value in data.options.solvers[0].options.iteritems()
                    #                         if not key == 'timelimit'))
                if not data.options.solvers[0].options_string is None:
                    opt.set_options(data.options.solvers[0].options_string)
                #
                # Use the solver manager to call the optimizer
                #
                results = solver_mngr.solve(instance, opt=opt, **keywords)
        else:
            #
            # Get the solver option arguments
            #
            if len(data.options.solvers[0].options) > 0 and not data.options.solvers[0].options_string is None:
                # If both 'options' and 'options_string' were specified, then create a
                # single options string that is passed to the solver.
                ostring = " ".join("%s=%s" % (key, value)
                                             for key, value in data.options.solvers[0].options.iteritems()
                                             if not value is None)
                keywords['options'] = ostring + ' ' + data.options.solvers[0].options_string
            elif len(data.options.solvers[0].options) > 0:
                keywords['options'] = data.options.solvers[0].options
            else:
                keywords['options'] = data.options.solvers[0].options_string
            #
            # If we're running remotely, then we pass the optimizer name to the solver
            # manager.
            #
            results = solver_mngr.solve(instance, opt=solver, **keywords)

    if (pympler_available is True) and \
       (data.options.runtime.profile_memory >= 1):
        global memory_data
        mem_used = muppy.get_size(muppy.get_objects())
        if mem_used > data.local.max_memory:
            data.local.max_memory = mem_used
        print("   Total memory = %d bytes following optimization" % mem_used)

    return pyutilib.misc.Options(results=results, opt=solver, local=data.local)
Пример #19
0
def apply_optimizer(data, instance=None):
    """
    Perform optimization with a concrete instance

    Required:
        instance:   Problem instance.

    Returned:
        results:    Optimization results.
        opt:        Optimizer object.
    """
    #
    if not data.options.runtime.logging == 'quiet':
        sys.stdout.write('[%8.2f] Applying solver\n' %
                         (time.time() - start_time))
        sys.stdout.flush()
    #
    #
    # Create Solver and Perform Optimization
    #
    solver = data.options.solvers[0].solver_name
    if solver is None:
        raise ValueError("Problem constructing solver:  no solver specified")

    if len(data.options.solvers[0].suffixes) > 0:
        for suffix_name in data.options.solvers[0].suffixes:
            if suffix_name[0] in ['"', "'"]:
                suffix_name = suffix_name[1:-1]
            # Don't redeclare the suffix if it already exists
            suffix = getattr(instance, suffix_name, None)
            if suffix is None:
                setattr(instance, suffix_name, Suffix(direction=Suffix.IMPORT))
            else:
                raise ValueError("Problem declaring solver suffix %s. A component "\
                                  "with that name already exists on model %s."
                                 % (suffix_name, instance.name))

    if getattr(data.options.solvers[0].options, 'timelimit', 0) == 0:
        data.options.solvers[0].options.timelimit = None
    #
    # Default results
    #
    results = None
    #
    # Figure out the type of solver manager
    #
    solver_mngr_name = None
    if data.options.solvers[0].manager is None:
        solver_mngr_name = 'serial'
    elif not data.options.solvers[0].manager in SolverManagerFactory:
        raise ValueError("Unknown solver manager %s" %
                         data.options.solvers[0].manager)
    else:
        solver_mngr_name = data.options.solvers[0].manager
    #
    # Create the solver manager
    #
    solver_mngr_kwds = {}
    with SolverManagerFactory(solver_mngr_name,
                              **solver_mngr_kwds) as solver_mngr:
        if solver_mngr is None:
            msg = "Problem constructing solver manager '%s'"
            raise ValueError(msg % str(data.options.solvers[0].manager))
        #
        # Setup keywords for the solve
        #
        keywords = {}
        if (data.options.runtime.keep_files or \
            data.options.postsolve.print_logfile):
            keywords['keepfiles'] = True
        if data.options.model.symbolic_solver_labels:
            keywords['symbolic_solver_labels'] = True
        if data.options.model.file_determinism != 1:
            keywords['file_determinism'] = data.options.model.file_determinism
        keywords['tee'] = data.options.runtime.stream_output
        keywords['timelimit'] = getattr(data.options.solvers[0].options,
                                        'timelimit', 0)
        keywords['report_timing'] = data.options.runtime.report_timing

        # FIXME: solver_io and executable are not being used
        #        in the case of a non-serial solver manager

        #
        # Call the solver
        #
        if solver_mngr_name == 'serial':
            #
            # If we're running locally, then we create the
            # optimizer and pass it into the solver manager.
            #
            sf_kwds = {}
            sf_kwds['solver_io'] = data.options.solvers[0].io_format
            if data.options.solvers[0].solver_executable is not None:
                sf_kwds['executable'] = data.options.solvers[
                    0].solver_executable
            with SolverFactory(solver, **sf_kwds) as opt:
                if opt is None:
                    raise ValueError("Problem constructing solver `%s`" %
                                     str(solver))

                for name in registered_callback:
                    opt.set_callback(name, registered_callback[name])

                if len(data.options.solvers[0].options) > 0:
                    opt.set_options(data.options.solvers[0].options)
                    #opt.set_options(" ".join("%s=%s" % (key, value)
                    #                         for key, value in data.options.solvers[0].options.iteritems()
                    #                         if not key == 'timelimit'))
                if not data.options.solvers[0].options_string is None:
                    opt.set_options(data.options.solvers[0].options_string)
                #
                # Use the solver manager to call the optimizer
                #
                results = solver_mngr.solve(instance, opt=opt, **keywords)
        else:
            #
            # Get the solver option arguments
            #
            if len(
                    data.options.solvers[0].options
            ) > 0 and not data.options.solvers[0].options_string is None:
                # If both 'options' and 'options_string' were specified, then create a
                # single options string that is passed to the solver.
                ostring = " ".join("%s=%s" % (key, value) for key, value in
                                   data.options.solvers[0].options.iteritems()
                                   if not value is None)
                keywords['options'] = ostring + ' ' + data.options.solvers[
                    0].options_string
            elif len(data.options.solvers[0].options) > 0:
                keywords['options'] = data.options.solvers[0].options
            else:
                keywords['options'] = data.options.solvers[0].options_string
            #
            # If we're running remotely, then we pass the optimizer name to the solver
            # manager.
            #
            results = solver_mngr.solve(instance, opt=solver, **keywords)

    if data.options.runtime.profile_memory >= 1 and pympler_available:
        global memory_data
        mem_used = pympler.muppy.get_size(pympler.muppy.get_objects())
        if mem_used > data.local.max_memory:
            data.local.max_memory = mem_used
        print("   Total memory = %d bytes following optimization" % mem_used)

    return Bunch(results=results, opt=solver, local=data.local)
Пример #20
0
# import the master a
# initialize the master instance.
mstr_mdl = import_file("master.py").model
mstr_inst = mstr_mdl.create_instance("master.dat")

# initialize the sub-problem instances.
sb_mdl = import_file("sub.py").model
sub_insts = []
sub_insts.append(
    sb_mdl.create_instance(name="sub1", \
                           filename="sub1.dat"))
sub_insts.append(
    sb_mdl.create_instance(name="sub2", \
                           filename="sub2.dat"))
# initialize the solver manager.
solver_manager = SolverManagerFactory("serial")

# miscellaneous initialization.
mstr_inst.Min_Stage2_cost = float("-Inf")

gap = float("Inf")
max_iterations = 50

# main benders loop.
for i in range(1, max_iterations + 1):
    print("\nIteration=%d" % (i))

    #solve the subproblem
    solve_all_instances(solver_manager, 'cplex', sub_insts)
    for instance in sub_insts:
        print("cost for scenario="+instance.name+" is"+\
Пример #21
0
class _ScenarioTreeManagerSolverWorker(ScenarioTreeManagerSolver,
                                       PySPConfiguredObject):

    @classmethod
    def _declare_options(cls, options=None):
        if options is None:
            options = PySPConfigBlock()

        # options for controlling the solver manager
        # (not the scenario tree manager)
        safe_declare_common_option(options,
                                   "solver_manager_pyro_host")
        safe_declare_common_option(options,
                                   "solver_manager_pyro_port")
        safe_declare_common_option(options,
                                   "solver_manager_pyro_shutdown")

        ScenarioTreePreprocessor._declare_options(options)

        return options

    @property
    def preprocessor(self):
        return self._preprocessor

    def __init__(self, *args, **kwds):
        if self.__class__ is _ScenarioTreeManagerSolverWorker:
            raise NotImplementedError(
                "%s is an abstract class for subclassing" % self.__class__)

        super(_ScenarioTreeManagerSolverWorker, self).__init__(*args, **kwds)
        # 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 self.manager is not None

        # solver related objects
        self._scenario_solvers = {}
        self._bundle_solvers = {}
        self._preprocessor = None
        self._solver_manager = None

        # there are situations in which it is valuable to snapshot /
        # store the solutions associated with the scenario
        # instances. for example, when one wants to use a warm-start
        # from a particular iteration solve, following a modification
        # and re-solve of the problem instances in a user-defined
        # callback. the following nested dictionary is intended to
        # serve that purpose. The nesting is dependent on whether
        # bundling and or phpyro is in use
        self._cached_solutions = {}
        self._cached_scenariotree_solutions = {}

        #
        # initialize the preprocessor
        #
        self._preprocessor = None
        if not self.get_option("disable_advanced_preprocessing"):
            self._preprocessor = ScenarioTreePreprocessor(self._options,
                                                          options_prefix=self._options_prefix)
        assert self._manager.preprocessor is None
        self._manager.preprocessor = self._preprocessor

        #
        # initialize the solver manager
        #
        self._solver_manager = SolverManagerFactory(
            self.get_option("solver_manager"),
            host=self.get_option('solver_manager_pyro_host'),
            port=self.get_option('solver_manager_pyro_port'))
        for scenario in self.manager.scenario_tree._scenarios:
            assert scenario._instance is not None
            solver = self._scenario_solvers[scenario.name] = \
                SolverFactory(self.get_option("solver"),
                              solver_io=self.get_option("solver_io"))
            if isinstance(solver, PersistentSolver) and \
               self.get_option("disable_advanced_preprocessing"):
                raise ValueError("Advanced preprocessing can not be disabled "
                                 "when persistent solvers are used")
            if self._preprocessor is not None:
                self._preprocessor.add_scenario(scenario,
                                                scenario._instance,
                                                solver)
        for bundle in self.manager.scenario_tree._scenario_bundles:
            solver = self._bundle_solvers[bundle.name] = \
                SolverFactory(self.get_option("solver"),
                              solver_io=self.get_option("solver_io"))
            if isinstance(solver, PersistentSolver) and \
               self.get_option("disable_advanced_preprocessing"):
                raise ValueError("Advanced preprocessing can not be disabled "
                                 "when persistent solvers are used")
            bundle_instance = \
                self.manager._bundle_binding_instance_map[bundle.name]
            if self._preprocessor is not None:
                self._preprocessor.add_bundle(bundle,
                                              bundle_instance,
                                              solver)

    #
    # Override some methods for ScenarioTreeManager that
    # were implemented by _ScenarioTreeManagerWorker:
    #

    def _close_impl(self):
        if (self._manager is not None) and \
           (self._manager.preprocessor is not None):
            assert self.preprocessor is self._manager.preprocessor
            for bundle in self.manager.scenario_tree._scenario_bundles:
                self._preprocessor.remove_bundle(bundle)
            for scenario in self.manager.scenario_tree._scenarios:
                assert scenario._instance is not None
                self._preprocessor.remove_scenario(scenario)
            self._manager.preprocessor = None
            self._preprocessor = None
        else:
            assert self._preprocessor is None

        if self._solver_manager is not None:
            #self._solver_manager.deactivate()
            self._solver_manager = None
            if self.get_option("solver_manager_pyro_shutdown"):
                print("Shutting down Pyro components for solver manager.")
                shutdown_pyro_components(
                    host=self.get_option("solver_manager_pyro_host"),
                    port=self.get_option("solver_manager_pyro_port"),
                    num_retries=0,
                    caller_name=self.__class__.__name__)
        #for solver in self._scenario_solvers.values():
        #    solver.deactivate()
        self._scenario_solvers = {}
        #for solver in self._bundle_solvers.values():
        #    solver.deactivate()
        self._bundle_solvers = {}
        self._preprocessor = None
        self._objective_sense = None

    #
    # Abstract methods for ScenarioTreeManagerSolver:
    #

    def _queue_object_solves(self,
                             object_type,
                             objects,
                             ephemeral_solver_options,
                             disable_warmstart):

        if self.get_option("verbose"):
            print("Queuing %s solves" % (object_type[:-1]))

        assert object_type in ('bundles', 'scenarios')

        solver_dict = None
        instance_dict = None
        modify_kwds_func = None
        if object_type == 'bundles':
            if objects is None:
                objects = self.manager.scenario_tree._scenario_bundle_map
            solver_dict = self._bundle_solvers
            instance_dict = self.manager._bundle_binding_instance_map
            for bundle_name in objects:
                for scenario_name in self.manager.scenario_tree.\
                    get_bundle(bundle_name).\
                       scenario_names:
                    self.manager.scenario_tree.get_scenario(scenario_name).\
                        _instance_objective.deactivate()
            if self.preprocessor is not None:
                self.preprocessor.preprocess_bundles(bundles=objects)
                modify_kwds_func = self.preprocessor.modify_bundle_solver_keywords
        else:
            if objects is None:
                objects = self.manager.scenario_tree._scenario_map
            solver_dict = self._scenario_solvers
            instance_dict = self.manager._instances
            if self.manager.scenario_tree.contains_bundles():
                for scenario_name in objects:
                    self.manager.scenario_tree.get_scenario(scenario_name).\
                        _instance_objective.activate()
            if self.preprocessor is not None:
                self.preprocessor.preprocess_scenarios(scenarios=objects)
                modify_kwds_func = self.preprocessor.modify_scenario_solver_keywords
        assert solver_dict is not None
        assert instance_dict is not None

        # setup common solve keywords
        common_kwds = {}
        common_kwds['tee'] = self.get_option("output_solver_log")
        common_kwds['keepfiles'] = self.get_option("keep_solver_files")
        common_kwds['symbolic_solver_labels'] = \
            self.get_option("symbolic_solver_labels")
        # we always manually load solutions, so we can
        # control error reporting and such
        common_kwds['load_solutions'] = False

        # Load solver options
        solver_options = {}
        if type(self.get_option("solver_options")) is tuple:
            solver_options.update(
                OptSolver._options_string_to_dict(
                    "".join(self.get_option("solver_options"))))
        else:
            solver_options.update(self.get_option("solver_options"))
        common_kwds['options'] = solver_options

        #
        # override "persistent" values that are included from this
        # classes registered options
        #
        if ephemeral_solver_options is not None:
            common_kwds['options'].update(ephemeral_solver_options)

        # maps action handles to subproblem names
        action_handle_data = {}
        for object_name in objects:

            if modify_kwds_func is not None:
                # be sure to modify a copy of the kwds
                solve_kwds = modify_kwds_func(object_name, dict(common_kwds))
            else:
                solve_kwds = common_kwds
            opt = solver_dict[object_name]
            instance = instance_dict[object_name]
            if (not self.get_option("disable_warmstart")) and \
               (not disable_warmstart) and \
               opt.warm_start_capable():
                new_action_handle = \
                    self._solver_manager.queue(instance,
                                               opt=opt,
                                               warmstart=True,
                                               **solve_kwds)
            else:
                new_action_handle = \
                    self._solver_manager.queue(instance,
                                               opt=opt,
                                               **solve_kwds)

            action_handle_data[new_action_handle] = object_name

        return self.manager.AsyncResult(
            self._solver_manager,
            action_handle_data=action_handle_data)
Пример #22
0
    def initialize(self, scenario_tree):
        import pyomo.environ
        import pyomo.solvers.plugins.smanager.phpyro

        init_start_time = time.time()

        print("Initializing Scenario Tree Manager")
        print("")

        if scenario_tree is None:
            raise ValueError("A scenario tree must be supplied to the "
                             "ScenarioTreeManager initialize() method")
        self._scenario_tree = scenario_tree

        # construct the solver manager.
        if self._options.verbose:
            print("Constructing solver manager of type=" +
                  self._options.solver_manager_type)
        self._solver_manager = \
            SolverManagerFactory(self._options.solver_manager_type,
                                 host=self._options.pyro_manager_hostname)
        if self._solver_manager is None:
            raise ValueError("Failed to create solver manager of "
                             "type=" + self._options.solver_manager_type)

        isPHPyro =  isinstance(self._solver_manager,
                               pyomo.solvers.plugins.\
                               smanager.phpyro.SolverManager_PHPyro)

        if isPHPyro:

            if self._scenario_tree.contains_bundles():
                num_jobs = len(self._scenario_tree._scenario_bundles)
                if not _OLD_OUTPUT:
                    print("Bundle solver jobs available: " + str(num_jobs))
            else:
                num_jobs = len(self._scenario_tree._scenarios)
                if not _OLD_OUTPUT:
                    print("Scenario solver jobs available: " + str(num_jobs))

            workers_expected = self._options.phpyro_required_workers
            if (workers_expected is None):
                workers_expected = num_jobs

            timeout = self._options.phpyro_workers_timeout if \
                      (self._options.phpyro_required_workers is None) else \
                      None

            self._solver_manager.acquire_workers(workers_expected, timeout)

        initialization_action_handles = []
        if isPHPyro:

            if self._options.verbose:
                print("Broadcasting requests to initialize "
                      "distributed scenario tree workers")

            initialization_action_handles.extend(
                scenariotreeserverutils.\
                initialize_scenariotree_workers(self))

            if self._options.verbose:
                print("Distributed scenario tree initialization "
                      "requests successfully transmitted")

        else:

            build_start_time = time.time()

            if not _OLD_OUTPUT:
                print("Constructing scenario tree instances")

            self._instances = \
                self._scenario_tree._scenario_instance_factory.\
                construct_instances_for_scenario_tree(
                    scenario_tree,
                    flatten_expressions=self._options.flatten_expressions,
                    report_timing=self._options.output_times,
                    preprocess=False)

            if self._options.verbose or self._options.output_times:
                print("Time to construct scenario instances=%.2f seconds" %
                      (time.time() - build_start_time))

            if not _OLD_OUTPUT:
                print("Linking instances into scenario tree")

            build_start_time = time.time()

            # with the scenario instances now available, link the
            # referenced objects directly into the scenario tree.
            self._scenario_tree.linkInInstances(
                self._instances,
                objective_sense=self._options.objective_sense,
                create_variable_ids=True)

            if self._options.verbose or self._options.output_times:
                print("Time link scenario tree with instances=%.2f seconds" %
                      (time.time() - build_start_time))

            if self._scenario_tree.contains_bundles():
                build_start_time = time.time()

                if self._options.verbose:
                    print("Forming binding instances for all scenario bundles")

                self._bundle_binding_instance_map.clear()
                self._bundle_scenario_instance_map.clear()

                if not self._scenario_tree.contains_bundles():
                    raise RuntimeError(
                        "Failed to create binding instances for scenario "
                        "bundles - no scenario bundles are defined!")

                for scenario_bundle in self._scenario_tree._scenario_bundles:

                    if self._options.verbose:
                        print(
                            "Creating binding instance for scenario bundle=%s"
                            % (scenario_bundle._name))

                    self._bundle_scenario_instance_map[
                        scenario_bundle._name] = {}
                    for scenario_name in scenario_bundle._scenario_names:
                        self._bundle_scenario_instance_map[scenario_bundle._name]\
                            [scenario_name] = self._instances[scenario_name]

                    # IMPORTANT: The bundle variable IDs must be idential to
                    #            those in the parent scenario tree - this is
                    #            critical for storing results, which occurs at
                    #            the full-scale scenario tree.

                    scenario_bundle._scenario_tree.linkInInstances(
                        self._instances,
                        create_variable_ids=False,
                        master_scenario_tree=self._scenario_tree,
                        initialize_solution_data=False)

                    bundle_ef_instance = create_ef_instance(
                        scenario_bundle._scenario_tree,
                        ef_instance_name=scenario_bundle._name,
                        verbose_output=self._verbose)

                    self._bundle_binding_instance_map[scenario_bundle._name] = \
                        bundle_ef_instance

                if self._output_times:
                    print("Scenario bundle construction time=%.2f seconds" %
                          (time.time() - build_start_time))

        # If specified, run the user script to collect aggregate
        # scenario data. This can slow down PH initialization as
        # syncronization across all phsolverservers is required
        if self._options.aggregate_cfgfile is not None:

            callback_name = "pysp_aggregategetter_callback"

            if isPHPyro:

                # Transmit invocation to phsolverservers
                print("Transmitting user aggregate callback invocations "
                      "to phsolverservers")
                if self._scenario_tree.contains_bundles():
                    for scenario_bundle in self._scenario_tree._scenario_bundles:
                        ah = scenariotreeserverutils.\
                             transmit_external_function_invocation_to_worker(
                                 self,
                                 scenario_bundle._name,
                                 self._callback_module_name[callback_name],
                                 callback_name,
                                 invocation_type=(scenariotreeserverutils.InvocationType.\
                                                  PerScenarioChainedInvocation),
                                 return_action_handle=True,
                                 function_args=(self._aggregate_user_data,))
                        while (1):
                            action_handle = self._solver_manager.wait_any()
                            if action_handle in initialization_action_handles:
                                initialization_action_handles.remove(
                                    action_handle)
                                self._solver_manager.get_results(action_handle)
                            elif action_handle == ah:
                                result = self._solver_manager.get_results(
                                    action_handle)
                                break
                        assert len(result) == 1
                        self._aggregate_user_data = result[0]

                else:
                    for scenario in self._scenario_tree._scenarios:
                        ah = scenariotreeserverutils.\
                             transmit_external_function_invocation_to_worker(
                                 self,
                                 scenario._name,
                                 self._callback_module_name[callback_name],
                                 callback_name,
                                 invocation_type=(scenariotreeserverutils.InvocationType.\
                                                  SingleInvocation),
                                 return_action_handle=True,
                                 function_args=(self._aggregate_user_data,))
                        while (1):
                            action_handle = self._solver_manager.wait_any()
                            if action_handle in initialization_action_handles:
                                initialization_action_handles.remove(
                                    action_handle)
                                self._solver_manager.get_results(action_handle)
                            elif action_handle == ah:
                                result = self._solver_manager.get_results(
                                    action_handle)
                                break
                        assert len(result) == 1
                        self._aggregate_user_data = result[0]

                # Transmit final aggregate state to phsolverservers
                print("Broadcasting final aggregate data to phsolverservers")
                initialization_action_handles.extend(
                    scenariotreeserverutils.transmit_external_function_invocation(
                        self,
                        "pyomo.pysp.ph",
                        "assign_aggregate_data",
                        invocation_type=(scenariotreeserverutils.InvocationType.\
                                         SingleInvocation),
                        return_action_handles=True,
                        function_args=(self._aggregate_user_data,)))

            else:

                print("Executing user aggregate getter callback function")
                for scenario in self._scenario_tree._scenarios:
                    result = self._callback_function[callback_name](
                        self, self._scenario_tree, scenario,
                        self._aggregate_user_data)
                    assert len(result) == 1
                    self._aggregate_user_data = result[0]

        # if specified, run the user script to initialize variable
        # bounds at their whim.
        if self._options.bounds_cfgfile is not None:

            callback_name = "pysp_boundsetter_callback"

            if isPHPyro:

                # Transmit invocation to phsolverservers
                print("Transmitting user bound callback invocations to "
                      "phsolverservers")
                if self._scenario_tree.contains_bundles():
                    for scenario_bundle in self._scenario_tree._scenario_bundles:
                        initialization_action_handles.append(
                            scenariotreeserverutils.\
                            transmit_external_function_invocation_to_worker(
                                self,
                                scenario_bundle._name,
                                self._callback_module_name[callback_name],
                                callback_name,
                                invocation_type=(scenariotreeserverutils.InvocationType.\
                                                 PerScenarioInvocation),
                                return_action_handle=True))
                else:
                    for scenario in self._scenario_tree._scenarios:
                        initialization_action_handles.append(
                            scenariotreeserverutils.\
                            transmit_external_function_invocation_to_worker(
                                self,
                                scenario._name,
                                self._callback_module_name[callback_name],
                                callback_name,
                                invocation_type=(scenariotreeserverutils.InvocationType.\
                                                 SingleInvocation),
                                return_action_handle=True))

            else:

                print("Executing user bound setter callback function")
                for scenario in self._scenario_tree._scenarios:
                    self._callback_function[callback_name](self,
                                                           self._scenario_tree,
                                                           scenario)

        # gather scenario tree data if not local
        if isPHPyro:

            if self._options.verbose:
                print("Broadcasting requests to collect scenario tree "
                      "instance data from PH solver servers")

            scenariotreeserverutils.\
                gather_scenario_tree_data(self,
                                          initialization_action_handles)
            assert len(initialization_action_handles) == 0

            if self._options.verbose:
                print("Scenario tree instance data successfully collected")

            if self._options.verbose:
                print("Broadcasting scenario tree id mapping"
                      "to PH solver servers")

            scenariotreeserverutils.transmit_scenario_tree_ids(self)

            if self._options.verbose:
                print("Scenario tree ids successfully sent")

        self._objective_sense = \
            self._scenario_tree._scenarios[0]._objective_sense

        if self._options.verbose:
            print("Scenario tree manager is successfully initialized")

        if self._options.output_times:
            print("Overall initialization time=%.2f seconds" %
                  (time.time() - init_start_time))

        # gather and report memory statistics (for leak
        # detection purposes) if specified.
        if (guppy_available) and (self._options.profile_memory >= 1):
            print(hpy().heap())

        # indicate that we're ready to run.
        self._initialized = True
Пример #23
0
    def initialize(self, scenario_tree):
        import pyomo.environ
        import pyomo.solvers.plugins.smanager.phpyro

        init_start_time = time.time()

        print("Initializing Scenario Tree Manager")
        print("")

        if scenario_tree is None:
            raise ValueError("A scenario tree must be supplied to the "
                             "ScenarioTreeManager initialize() method")
        self._scenario_tree = scenario_tree

        # construct the solver manager.
        if self._options.verbose:
            print("Constructing solver manager of type="
                  +self._options.solver_manager_type)
        self._solver_manager = \
            SolverManagerFactory(self._options.solver_manager_type,
                                 host=self._options.pyro_manager_hostname)
        if self._solver_manager is None:
            raise ValueError("Failed to create solver manager of "
                             "type="+self._options.solver_manager_type)

        isPHPyro =  isinstance(self._solver_manager,
                               pyomo.solvers.plugins.\
                               smanager.phpyro.SolverManager_PHPyro)

        if isPHPyro:

            if self._scenario_tree.contains_bundles():
                num_jobs = len(self._scenario_tree._scenario_bundles)
                if not _OLD_OUTPUT:
                    print("Bundle solver jobs available: "+str(num_jobs))
            else:
                num_jobs = len(self._scenario_tree._scenarios)
                if not _OLD_OUTPUT:
                    print("Scenario solver jobs available: "+str(num_jobs))

            workers_expected = self._options.phpyro_required_workers
            if (workers_expected is None):
                workers_expected = num_jobs

            timeout = self._options.phpyro_workers_timeout if \
                      (self._options.phpyro_required_workers is None) else \
                      None

            self._solver_manager.acquire_workers(workers_expected,
                                                 timeout)

        initialization_action_handles = []
        if isPHPyro:

            if self._options.verbose:
                print("Broadcasting requests to initialize "
                      "distributed scenario tree workers")

            initialization_action_handles.extend(
                scenariotreeserverutils.\
                initialize_scenariotree_workers(self))

            if self._options.verbose:
                print("Distributed scenario tree initialization "
                      "requests successfully transmitted")

        else:

            build_start_time = time.time()

            if not _OLD_OUTPUT:
                print("Constructing scenario tree instances")

            self._instances = \
                self._scenario_tree._scenario_instance_factory.\
                construct_instances_for_scenario_tree(
                    scenario_tree,
                    flatten_expressions=self._options.flatten_expressions,
                    report_timing=self._options.output_times,
                    preprocess=False)

            if self._options.verbose or self._options.output_times:
                print("Time to construct scenario instances=%.2f seconds"
                      % (time.time() - build_start_time))

            if not _OLD_OUTPUT:
                print("Linking instances into scenario tree")

            build_start_time = time.time()

            # with the scenario instances now available, link the
            # referenced objects directly into the scenario tree.
            self._scenario_tree.linkInInstances(
                self._instances,
                objective_sense=self._options.objective_sense,
                create_variable_ids=True)

            if self._options.verbose or self._options.output_times:
                print("Time link scenario tree with instances=%.2f seconds"
                      % (time.time() - build_start_time))

            if self._scenario_tree.contains_bundles():
                build_start_time = time.time()

                if self._options.verbose:
                    print("Forming binding instances for all scenario bundles")

                self._bundle_binding_instance_map.clear()
                self._bundle_scenario_instance_map.clear()

                if not self._scenario_tree.contains_bundles():
                    raise RuntimeError("Failed to create binding instances for scenario "
                                       "bundles - no scenario bundles are defined!")

                for scenario_bundle in self._scenario_tree._scenario_bundles:

                    if self._options.verbose:
                        print("Creating binding instance for scenario bundle=%s"
                              % (scenario_bundle._name))

                    self._bundle_scenario_instance_map[scenario_bundle._name] = {}
                    for scenario_name in scenario_bundle._scenario_names:
                        self._bundle_scenario_instance_map[scenario_bundle._name]\
                            [scenario_name] = self._instances[scenario_name]

                    # IMPORTANT: The bundle variable IDs must be idential to
                    #            those in the parent scenario tree - this is
                    #            critical for storing results, which occurs at
                    #            the full-scale scenario tree.

                    scenario_bundle._scenario_tree.linkInInstances(
                        self._instances,
                        create_variable_ids=False,
                        master_scenario_tree=self._scenario_tree,
                        initialize_solution_data=False)

                    bundle_ef_instance = create_ef_instance(
                        scenario_bundle._scenario_tree,
                        ef_instance_name=scenario_bundle._name,
                        verbose_output=self._verbose)

                    self._bundle_binding_instance_map[scenario_bundle._name] = \
                        bundle_ef_instance

                if self._output_times:
                    print("Scenario bundle construction time=%.2f seconds"
                          % (time.time() - build_start_time))

        # If specified, run the user script to collect aggregate
        # scenario data. This can slow down PH initialization as
        # syncronization across all phsolverservers is required
        if self._options.aggregate_cfgfile is not None:

            callback_name = "pysp_aggregategetter_callback"

            if isPHPyro:

                # Transmit invocation to phsolverservers
                print("Transmitting user aggregate callback invocations "
                      "to phsolverservers")
                if self._scenario_tree.contains_bundles():
                    for scenario_bundle in self._scenario_tree._scenario_bundles:
                        ah = scenariotreeserverutils.\
                             transmit_external_function_invocation_to_worker(
                                 self,
                                 scenario_bundle._name,
                                 self._callback_module_name[callback_name],
                                 callback_name,
                                 invocation_type=(scenariotreeserverutils.InvocationType.\
                                                  PerScenarioChainedInvocation),
                                 return_action_handle=True,
                                 function_args=(self._aggregate_user_data,))
                        while(1):
                            action_handle = self._solver_manager.wait_any()
                            if action_handle in initialization_action_handles:
                                initialization_action_handles.remove(action_handle)
                                self._solver_manager.get_results(action_handle)
                            elif action_handle == ah:
                                result = self._solver_manager.get_results(action_handle)
                                break
                        assert len(result) == 1
                        self._aggregate_user_data = result[0]

                else:
                    for scenario in self._scenario_tree._scenarios:
                        ah = scenariotreeserverutils.\
                             transmit_external_function_invocation_to_worker(
                                 self,
                                 scenario._name,
                                 self._callback_module_name[callback_name],
                                 callback_name,
                                 invocation_type=(scenariotreeserverutils.InvocationType.\
                                                  SingleInvocation),
                                 return_action_handle=True,
                                 function_args=(self._aggregate_user_data,))
                        while(1):
                            action_handle = self._solver_manager.wait_any()
                            if action_handle in initialization_action_handles:
                                initialization_action_handles.remove(action_handle)
                                self._solver_manager.get_results(action_handle)
                            elif action_handle == ah:
                                result = self._solver_manager.get_results(action_handle)
                                break
                        assert len(result) == 1
                        self._aggregate_user_data = result[0]

                # Transmit final aggregate state to phsolverservers
                print("Broadcasting final aggregate data to phsolverservers")
                initialization_action_handles.extend(
                    scenariotreeserverutils.transmit_external_function_invocation(
                        self,
                        "pyomo.pysp.ph",
                        "assign_aggregate_data",
                        invocation_type=(scenariotreeserverutils.InvocationType.\
                                         SingleInvocation),
                        return_action_handles=True,
                        function_args=(self._aggregate_user_data,)))

            else:

                print("Executing user aggregate getter callback function")
                for scenario in self._scenario_tree._scenarios:
                    result = self._callback_function[callback_name](
                        self,
                        self._scenario_tree,
                        scenario,
                        self._aggregate_user_data)
                    assert len(result) == 1
                    self._aggregate_user_data = result[0]

        # if specified, run the user script to initialize variable
        # bounds at their whim.
        if self._options.bounds_cfgfile is not None:

            callback_name = "pysp_boundsetter_callback"

            if isPHPyro:

                # Transmit invocation to phsolverservers
                print("Transmitting user bound callback invocations to "
                      "phsolverservers")
                if self._scenario_tree.contains_bundles():
                    for scenario_bundle in self._scenario_tree._scenario_bundles:
                        initialization_action_handles.append(
                            scenariotreeserverutils.\
                            transmit_external_function_invocation_to_worker(
                                self,
                                scenario_bundle._name,
                                self._callback_module_name[callback_name],
                                callback_name,
                                invocation_type=(scenariotreeserverutils.InvocationType.\
                                                 PerScenarioInvocation),
                                return_action_handle=True))
                else:
                    for scenario in self._scenario_tree._scenarios:
                        initialization_action_handles.append(
                            scenariotreeserverutils.\
                            transmit_external_function_invocation_to_worker(
                                self,
                                scenario._name,
                                self._callback_module_name[callback_name],
                                callback_name,
                                invocation_type=(scenariotreeserverutils.InvocationType.\
                                                 SingleInvocation),
                                return_action_handle=True))

            else:

                print("Executing user bound setter callback function")
                for scenario in self._scenario_tree._scenarios:
                    self._callback_function[callback_name](
                        self,
                        self._scenario_tree,
                        scenario)

        # gather scenario tree data if not local
        if isPHPyro:

            if self._options.verbose:
                print("Broadcasting requests to collect scenario tree "
                      "instance data from PH solver servers")

            scenariotreeserverutils.\
                gather_scenario_tree_data(self,
                                          initialization_action_handles)
            assert len(initialization_action_handles) == 0

            if self._options.verbose:
                print("Scenario tree instance data successfully collected")

            if self._options.verbose:
                print("Broadcasting scenario tree id mapping"
                      "to PH solver servers")

            scenariotreeserverutils.transmit_scenario_tree_ids(self)

            if self._options.verbose:
                print("Scenario tree ids successfully sent")

        self._objective_sense = \
            self._scenario_tree._scenarios[0]._objective_sense

        if self._options.verbose:
            print("Scenario tree manager is successfully initialized")

        if self._options.output_times:
            print("Overall initialization time=%.2f seconds"
                  % (time.time() - init_start_time))

        # gather and report memory statistics (for leak
        # detection purposes) if specified.
        if (guppy_available) and (self._options.profile_memory >= 1):
            print(hpy().heap())

        # indicate that we're ready to run.
        self._initialized = True