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Pyomo: Collect variable bounds, obj_coeff, value, type

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master
Alinson S. Xavier 5 years ago
parent 6b15337e4c
commit 3cfadf4e97
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GPG Key ID: DCA0DAD4D2F58624
6 changed files with 163 additions and 68 deletions
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9
miplearn/solvers/gurobi.py
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@ -26,6 +26,7 @@ from miplearn.types import (
UserCutCallback, UserCutCallback,
Solution, Solution,
VariableName, VariableName,
Category,
) )
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
@ -67,6 +68,7 @@ class GurobiSolver(InternalSolver):
self.lazy_cb_frequency = lazy_cb_frequency self.lazy_cb_frequency = lazy_cb_frequency
self._bin_vars: List["gurobipy.Var"] = [] self._bin_vars: List["gurobipy.Var"] = []
self._varname_to_var: Dict[str, "gurobipy.Var"] = {} self._varname_to_var: Dict[str, "gurobipy.Var"] = {}
self._original_vtype: Dict["gurobipy.Var", str] = {}
self._dirty = True self._dirty = True
self._has_lp_solution = False self._has_lp_solution = False
self._has_mip_solution = False self._has_mip_solution = False
@ -101,6 +103,7 @@ class GurobiSolver(InternalSolver):
def _update_vars(self) -> None: def _update_vars(self) -> None:
assert self.model is not None assert self.model is not None
self._varname_to_var.clear() self._varname_to_var.clear()
self._original_vtype = {}
self._bin_vars.clear() self._bin_vars.clear()
for var in self.model.getVars(): for var in self.model.getVars():
assert var.varName not in self._varname_to_var, ( assert var.varName not in self._varname_to_var, (
@ -112,6 +115,7 @@ class GurobiSolver(InternalSolver):
"Only binary and continuous variables are currently supported. " "Only binary and continuous variables are currently supported. "
"Variable {var.varName} has type {var.vtype}." "Variable {var.varName} has type {var.vtype}."
) )
self._original_vtype[var] = var.vtype
if var.vtype == "B": if var.vtype == "B":
self._bin_vars.append(var) self._bin_vars.append(var)
@ -433,7 +437,7 @@ class GurobiSolver(InternalSolver):
var.lower_bound = gp_var.lb var.lower_bound = gp_var.lb
var.upper_bound = gp_var.ub var.upper_bound = gp_var.ub
var.obj_coeff = gp_var.obj var.obj_coeff = gp_var.obj
var.type = gp_var.vtype var.type = self._original_vtype[gp_var]
if self._has_lp_solution: if self._has_lp_solution:
var.reduced_cost = gp_var.rc var.reduced_cost = gp_var.rc
@ -587,8 +591,9 @@ class GurobiTestInstanceKnapsack(PyomoTestInstanceKnapsack):
model = gp.Model("Knapsack") model = gp.Model("Knapsack")
n = len(self.weights) n = len(self.weights)
x = model.addVars(n, vtype=GRB.BINARY, name="x") x = model.addVars(n, vtype=GRB.BINARY, name="x")
z = model.addVar(vtype=GRB.CONTINUOUS, name="z", ub=self.capacity)
model.addConstr( model.addConstr(
gp.quicksum(x[i] * self.weights[i] for i in range(n)) <= self.capacity, gp.quicksum(x[i] * self.weights[i] for i in range(n)) == z,
"eq_capacity", "eq_capacity",
) )
model.setObjective( model.setObjective(

1
miplearn/solvers/learning.py
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@ -253,7 +253,6 @@ class LearningSolver:
# ------------------------------------------------------- # -------------------------------------------------------
logger.info("Extracting features (after-mip)...") logger.info("Extracting features (after-mip)...")
features = FeaturesExtractor(self.internal_solver).extract(instance) features = FeaturesExtractor(self.internal_solver).extract(instance)
features.lp_solve = lp_stats
features.mip_solve = mip_stats features.mip_solve = mip_stats
instance.features_after_mip.append(features) instance.features_after_mip.append(features)

99
miplearn/solvers/pyomo/base.py
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@ -12,7 +12,7 @@ import numpy as np
import pyomo import pyomo
from overrides import overrides from overrides import overrides
from pyomo import environ as pe from pyomo import environ as pe
from pyomo.core import Var, Suffix from pyomo.core import Var, Suffix, Objective
from pyomo.core.base import _GeneralVarData from pyomo.core.base import _GeneralVarData
from pyomo.core.base.constraint import ConstraintList from pyomo.core.base.constraint import ConstraintList
from pyomo.core.expr.numeric_expr import SumExpression, MonomialTermExpression from pyomo.core.expr.numeric_expr import SumExpression, MonomialTermExpression
@ -64,6 +64,7 @@ class BasePyomoSolver(InternalSolver):
self._termination_condition: str = "" self._termination_condition: str = ""
self._has_lp_solution = False self._has_lp_solution = False
self._has_mip_solution = False self._has_mip_solution = False
self._obj: Dict[str, float] = {}
for (key, value) in params.items(): for (key, value) in params.items():
self._pyomo_solver.options[key] = value self._pyomo_solver.options[key] = value
@ -223,6 +224,9 @@ class BasePyomoSolver(InternalSolver):
self._all_vars += [var[idx]] self._all_vars += [var[idx]]
if var[idx].domain == pyomo.core.base.set_types.Binary: if var[idx].domain == pyomo.core.base.set_types.Binary:
self._bin_vars += [var[idx]] self._bin_vars += [var[idx]]
for obj in self.model.component_objects(Objective):
self._obj = self._parse_pyomo_expr(obj.expr)
break
def _update_constrs(self) -> None: def _update_constrs(self) -> None:
assert self.model is not None assert self.model is not None
@ -371,11 +375,42 @@ class BasePyomoSolver(InternalSolver):
for var in self.model.component_objects(pyomo.core.Var): for var in self.model.component_objects(pyomo.core.Var):
for idx in var: for idx in var:
varname = f"{var}[{idx}]" varname = f"{var}[{idx}]"
if idx is None:
varname = str(var)
variables[varname] = self._parse_pyomo_variable(var[idx]) variables[varname] = self._parse_pyomo_variable(var[idx])
return variables return variables
def _parse_pyomo_variable(self, var: pyomo.core.Var) -> Variable: def _parse_pyomo_variable(self, var: pyomo.core.Var) -> Variable:
return Variable() # Variable type
vtype: Optional[str] = None
if var.domain == pyomo.core.Binary:
vtype = "B"
elif var.domain in [
pyomo.core.Reals,
pyomo.core.NonNegativeReals,
pyomo.core.NonPositiveReals,
pyomo.core.NegativeReals,
pyomo.core.PositiveReals,
]:
vtype = "C"
if vtype is None:
raise Exception(f"unknown variable domain: {var.domain}")
# Bounds
lb, ub = var.bounds
# Objective coefficient
obj_coeff = 0.0
if var.name in self._obj:
obj_coeff = self._obj[var.name]
return Variable(
value=var.value,
type=vtype,
lower_bound=float(lb),
upper_bound=float(ub),
obj_coeff=obj_coeff,
)
@overrides @overrides
def get_constraints(self) -> Dict[str, Constraint]: def get_constraints(self) -> Dict[str, Constraint]:
@ -408,10 +443,10 @@ class BasePyomoSolver(InternalSolver):
assert ( assert (
(not has_lb) or (not has_ub) or pyomo_constr.upper() == pyomo_constr.lower() (not has_lb) or (not has_ub) or pyomo_constr.upper() == pyomo_constr.lower()
), "range constraints not supported" ), "range constraints not supported"
if has_lb: if not has_ub:
constr.sense = ">" constr.sense = ">"
constr.rhs = pyomo_constr.lower() constr.rhs = pyomo_constr.lower()
elif has_ub: elif not has_lb:
constr.sense = "<" constr.sense = "<"
constr.rhs = pyomo_constr.upper() constr.rhs = pyomo_constr.upper()
else: else:
@ -419,22 +454,7 @@ class BasePyomoSolver(InternalSolver):
constr.rhs = pyomo_constr.upper() constr.rhs = pyomo_constr.upper()
# Extract LHS # Extract LHS
lhs = {} constr.lhs = self._parse_pyomo_expr(pyomo_constr.body)
if isinstance(pyomo_constr.body, SumExpression):
for term in pyomo_constr.body._args_:
if isinstance(term, MonomialTermExpression):
lhs[term._args_[1].name] = term._args_[0]
elif isinstance(term, _GeneralVarData):
lhs[term.name] = 1.0
else:
raise Exception(f"Unknown term type: {term.__class__.__name__}")
elif isinstance(pyomo_constr.body, _GeneralVarData):
lhs[pyomo_constr.body.name] = 1.0
else:
raise Exception(
f"Unknown expression type: {pyomo_constr.body.__class__.__name__}"
)
constr.lhs = lhs
# Extract solution attributes # Extract solution attributes
if self._has_lp_solution: if self._has_lp_solution:
@ -446,6 +466,22 @@ class BasePyomoSolver(InternalSolver):
# Build constraint # Build constraint
return constr return constr
def _parse_pyomo_expr(self, expr):
lhs = {}
if isinstance(expr, SumExpression):
for term in expr._args_:
if isinstance(term, MonomialTermExpression):
lhs[term._args_[1].name] = float(term._args_[0])
elif isinstance(term, _GeneralVarData):
lhs[term.name] = 1.0
else:
raise Exception(f"Unknown term type: {term.__class__.__name__}")
elif isinstance(expr, _GeneralVarData):
lhs[expr.name] = 1.0
else:
raise Exception(f"Unknown expression type: {expr.__class__.__name__}")
return lhs
@overrides @overrides
def are_callbacks_supported(self) -> bool: def are_callbacks_supported(self) -> bool:
return False return False
@ -453,23 +489,20 @@ class BasePyomoSolver(InternalSolver):
@overrides @overrides
def get_constraint_attrs(self) -> List[str]: def get_constraint_attrs(self) -> List[str]:
return [ return [
"category",
"dual_value", "dual_value",
"lazy", "lazy",
"lhs", "lhs",
"rhs", "rhs",
"sense", "sense",
"slack", "slack",
"user_features",
] ]
@overrides @overrides
def get_variable_attrs(self) -> List[str]: def get_variable_attrs(self) -> List[str]:
return [ return [
# "basis_status", # "basis_status",
# "category", "lower_bound",
# "lower_bound", "obj_coeff",
# "obj_coeff",
# "reduced_cost", # "reduced_cost",
# "sa_lb_down", # "sa_lb_down",
# "sa_lb_up", # "sa_lb_up",
@ -477,10 +510,9 @@ class BasePyomoSolver(InternalSolver):
# "sa_obj_up", # "sa_obj_up",
# "sa_ub_down", # "sa_ub_down",
# "sa_ub_up", # "sa_ub_up",
# "type", "type",
# "upper_bound", "upper_bound",
# "user_features", "value",
# "value",
] ]
@ -529,12 +561,13 @@ class PyomoTestInstanceKnapsack(Instance):
model = pe.ConcreteModel() model = pe.ConcreteModel()
items = range(len(self.weights)) items = range(len(self.weights))
model.x = pe.Var(items, domain=pe.Binary) model.x = pe.Var(items, domain=pe.Binary)
model.z = pe.Var(domain=pe.Reals, bounds=(0, self.capacity))
model.OBJ = pe.Objective( model.OBJ = pe.Objective(
expr=sum(model.x[v] * self.prices[v] for v in items), expr=sum(model.x[v] * self.prices[v] for v in items),
sense=pe.maximize, sense=pe.maximize,
) )
model.eq_capacity = pe.Constraint( model.eq_capacity = pe.Constraint(
expr=sum(model.x[v] * self.weights[v] for v in items) <= self.capacity expr=sum(model.x[v] * self.weights[v] for v in items) == model.z
) )
return model return model
@ -552,3 +585,9 @@ class PyomoTestInstanceKnapsack(Instance):
self.weights[item], self.weights[item],
self.prices[item], self.prices[item],
] ]
@overrides
def get_variable_category(self, var_name: VariableName) -> Optional[Category]:
if var_name.startswith("x"):
return "default"
return None

84
miplearn/solvers/tests/__init__.py
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@ -117,6 +117,12 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
type="B", type="B",
upper_bound=1.0, upper_bound=1.0,
), ),
"z": Variable(
lower_bound=0.0,
obj_coeff=0.0,
type="C",
upper_bound=67.0,
),
}, },
), ),
) )
@ -127,9 +133,9 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
{ {
"eq_capacity": Constraint( "eq_capacity": Constraint(
lazy=False, lazy=False,
lhs={"x[0]": 23.0, "x[1]": 26.0, "x[2]": 20.0, "x[3]": 18.0}, lhs={"x[0]": 23.0, "x[1]": 26.0, "x[2]": 20.0, "x[3]": 18.0, "z": -1.0},
rhs=67.0, rhs=0.0,
sense="<", sense="=",
) )
}, },
) )
@ -161,7 +167,7 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
sa_obj_up=inf, sa_obj_up=inf,
sa_ub_down=0.913043, sa_ub_down=0.913043,
sa_ub_up=2.043478, sa_ub_up=2.043478,
type="C", type="B",
upper_bound=1.0, upper_bound=1.0,
value=1.0, value=1.0,
), ),
@ -176,7 +182,7 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
sa_obj_up=570.869565, sa_obj_up=570.869565,
sa_ub_down=0.923077, sa_ub_down=0.923077,
sa_ub_up=inf, sa_ub_up=inf,
type="C", type="B",
upper_bound=1.0, upper_bound=1.0,
value=0.923077, value=0.923077,
), ),
@ -191,7 +197,7 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
sa_obj_up=inf, sa_obj_up=inf,
sa_ub_down=0.9, sa_ub_down=0.9,
sa_ub_up=2.2, sa_ub_up=2.2,
type="C", type="B",
upper_bound=1.0, upper_bound=1.0,
value=1.0, value=1.0,
), ),
@ -206,10 +212,25 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
sa_obj_up=243.692308, sa_obj_up=243.692308,
sa_ub_down=0.0, sa_ub_down=0.0,
sa_ub_up=inf, sa_ub_up=inf,
type="C", type="B",
upper_bound=1.0, upper_bound=1.0,
value=0.0, value=0.0,
), ),
"z": Variable(
basis_status="U",
lower_bound=0.0,
obj_coeff=0.0,
reduced_cost=13.538462,
sa_lb_down=-inf,
sa_lb_up=67.0,
sa_obj_down=-13.538462,
sa_obj_up=inf,
sa_ub_down=43.0,
sa_ub_up=69.0,
type="C",
upper_bound=67.0,
value=67.0,
),
}, },
), ),
) )
@ -221,15 +242,21 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
solver, solver,
{ {
"eq_capacity": Constraint( "eq_capacity": Constraint(
basis_status="N",
dual_value=13.538462,
lazy=False, lazy=False,
lhs={"x[0]": 23.0, "x[1]": 26.0, "x[2]": 20.0, "x[3]": 18.0}, lhs={
rhs=67.0, "x[0]": 23.0,
sense="<", "x[1]": 26.0,
"x[2]": 20.0,
"x[3]": 18.0,
"z": -1.0,
},
rhs=0.0,
sa_rhs_down=-24.0,
sa_rhs_up=1.9999999999999987,
sense="=",
slack=0.0, slack=0.0,
dual_value=13.538462,
sa_rhs_down=43.0,
sa_rhs_up=69.0,
basis_status="N",
) )
}, },
), ),
@ -238,9 +265,6 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
# Solve MIP # Solve MIP
mip_stats = solver.solve( mip_stats = solver.solve(
tee=True, tee=True,
iteration_cb=None,
lazy_cb=None,
user_cut_cb=None,
) )
assert not solver.is_infeasible() assert not solver.is_infeasible()
assert mip_stats.mip_log is not None assert mip_stats.mip_log is not None
@ -289,6 +313,13 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
upper_bound=1.0, upper_bound=1.0,
value=1.0, value=1.0,
), ),
"z": Variable(
lower_bound=0.0,
obj_coeff=0.0,
type="C",
upper_bound=67.0,
value=61.0,
),
}, },
), ),
) )
@ -298,11 +329,12 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
_round_constraints(solver.get_constraints()), _round_constraints(solver.get_constraints()),
{ {
"eq_capacity": Constraint( "eq_capacity": Constraint(
lhs={"x[0]": 23.0, "x[1]": 26.0, "x[2]": 20.0, "x[3]": 18.0}, lazy=False,
rhs=67.0, lhs={"x[0]": 23.0, "x[1]": 26.0, "x[2]": 20.0, "x[3]": 18.0, "z": -1.0},
sense="<", rhs=0.0,
slack=6.0, sense="=",
), slack=0.0,
)
}, },
) )
@ -317,11 +349,13 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
_round_constraints(solver.get_constraints()), _round_constraints(solver.get_constraints()),
{ {
"eq_capacity": Constraint( "eq_capacity": Constraint(
lhs={"x[0]": 23.0, "x[1]": 26.0, "x[2]": 20.0, "x[3]": 18.0}, lazy=False,
rhs=67.0, lhs={"x[0]": 23.0, "x[1]": 26.0, "x[2]": 20.0, "x[3]": 18.0, "z": -1.0},
sense="<", rhs=0.0,
sense="=",
), ),
"cut": Constraint( "cut": Constraint(
lazy=False,
lhs={"x[0]": 1.0}, lhs={"x[0]": 1.0},
rhs=0.0, rhs=0.0,
sense="<", sense="<",

2
tests/solvers/test_learning_solver.py
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@ -92,7 +92,7 @@ def test_parallel_solve(
for instance in instances: for instance in instances:
data = instance.training_data[0] data = instance.training_data[0]
assert data.solution is not None assert data.solution is not None
assert len(data.solution.keys()) == 4 assert len(data.solution.keys()) == 5
def test_solve_fit_from_disk( def test_solve_fit_from_disk(

36
tests/test_features.py
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@ -41,7 +41,7 @@ def test_knapsack() -> None:
sa_obj_up=inf, sa_obj_up=inf,
sa_ub_down=0.913043, sa_ub_down=0.913043,
sa_ub_up=2.043478, sa_ub_up=2.043478,
type="C", type="B",
upper_bound=1.0, upper_bound=1.0,
user_features=[23.0, 505.0], user_features=[23.0, 505.0],
value=1.0, value=1.0,
@ -59,7 +59,7 @@ def test_knapsack() -> None:
sa_obj_up=570.869565, sa_obj_up=570.869565,
sa_ub_down=0.923077, sa_ub_down=0.923077,
sa_ub_up=inf, sa_ub_up=inf,
type="C", type="B",
upper_bound=1.0, upper_bound=1.0,
user_features=[26.0, 352.0], user_features=[26.0, 352.0],
value=0.923077, value=0.923077,
@ -86,7 +86,7 @@ def test_knapsack() -> None:
sa_obj_up=inf, sa_obj_up=inf,
sa_ub_down=0.9, sa_ub_down=0.9,
sa_ub_up=2.2, sa_ub_up=2.2,
type="C", type="B",
upper_bound=1.0, upper_bound=1.0,
user_features=[20.0, 458.0], user_features=[20.0, 458.0],
value=1.0, value=1.0,
@ -104,12 +104,30 @@ def test_knapsack() -> None:
sa_obj_up=243.692308, sa_obj_up=243.692308,
sa_ub_down=0.0, sa_ub_down=0.0,
sa_ub_up=inf, sa_ub_up=inf,
type="C", type="B",
upper_bound=1.0, upper_bound=1.0,
user_features=[18.0, 220.0], user_features=[18.0, 220.0],
value=0.0, value=0.0,
alvarez_2017=[1.0, 0.143322, 0.0, 0.0, 1.0, -1.0, 46.051702, 3.16515], alvarez_2017=[1.0, 0.143322, 0.0, 0.0, 1.0, -1.0, 46.051702, 3.16515],
), ),
"z": Variable(
basis_status="U",
category=None,
lower_bound=0.0,
obj_coeff=0.0,
reduced_cost=13.538462,
sa_lb_down=-inf,
sa_lb_up=67.0,
sa_obj_down=-13.538462,
sa_obj_up=inf,
sa_ub_down=43.0,
sa_ub_up=69.0,
type="C",
upper_bound=67.0,
user_features=None,
value=67.0,
alvarez_2017=[0.0, 0.0, 0.0, 0.0, 1.0, -1.0, 0.0, 0.0],
),
}, },
) )
assert_equals( assert_equals(
@ -120,11 +138,11 @@ def test_knapsack() -> None:
category="eq_capacity", category="eq_capacity",
dual_value=13.538462, dual_value=13.538462,
lazy=False, lazy=False,
lhs={"x[0]": 23.0, "x[1]": 26.0, "x[2]": 20.0, "x[3]": 18.0}, lhs={"x[0]": 23.0, "x[1]": 26.0, "x[2]": 20.0, "x[3]": 18.0, "z": -1.0},
rhs=67.0, rhs=0.0,
sa_rhs_down=43.0, sa_rhs_down=-24.0,
sa_rhs_up=69.0, sa_rhs_up=1.9999999999999987,
sense="<", sense="=",
slack=0.0, slack=0.0,
user_features=[0.0], user_features=[0.0],
) )

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