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Add more variable features

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This commit is contained in:
Alinson S. Xavier
2021-04-10 18:29:38 -05:00
parent 5e1f26e4b0
commit 733c8299e0
8 changed files with 331 additions and 61 deletions
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71
miplearn/solvers/gurobi.py
View File

@@ -10,7 +10,7 @@ from typing import List, Any, Dict, Optional, Hashable
from overrides import overrides
from miplearn.features import Constraint
from miplearn.features import Constraint, Variable
from miplearn.instance.base import Instance
from miplearn.solvers import _RedirectOutput
from miplearn.solvers.internal import (
@@ -415,6 +415,49 @@ class GurobiSolver(InternalSolver):
capacity=67.0,
)
@overrides
def get_variables(self) -> Dict[str, Variable]:
assert self.model is not None
variables = {}
for gp_var in self.model.getVars():
name = gp_var.varName
assert len(name) > 0, f"empty variable name detected"
assert name not in variables, f"duplicated variable name detected: {name}"
var = self._parse_gurobi_var(gp_var)
variables[name] = var
return variables
def _parse_gurobi_var(self, gp_var: Any) -> Variable:
assert self.model is not None
var = Variable()
var.lower_bound = gp_var.lb
var.upper_bound = gp_var.ub
var.obj_coeff = gp_var.obj
var.type = gp_var.vtype
if self._has_lp_solution:
var.reduced_cost = gp_var.rc
var.sa_obj_up = gp_var.saobjUp
var.sa_obj_down = gp_var.saobjLow
var.sa_ub_up = gp_var.saubUp
var.sa_ub_down = gp_var.saubLow
var.sa_lb_up = gp_var.salbUp
var.sa_lb_down = gp_var.salbLow
vbasis = gp_var.vbasis
if vbasis == 0:
var.basis_status = "B"
elif vbasis == -1:
var.basis_status = "L"
elif vbasis == -2:
var.basis_status = "U"
elif vbasis == -3:
var.basis_status = "S"
else:
raise Exception(f"unknown vbasis: {vbasis}")
if self._has_lp_solution or self._has_mip_solution:
var.value = gp_var.x
return var
@overrides
def get_constraints(self) -> Dict[str, Constraint]:
assert self.model is not None
@@ -443,11 +486,11 @@ class GurobiSolver(InternalSolver):
if self._has_lp_solution:
constr.dual_value = gp_constr.pi
constr.sa_rhs_up = gp_constr.sarhsup
constr.sa_rhs_low = gp_constr.sarhslow
constr.sa_rhs_down = gp_constr.sarhslow
if gp_constr.cbasis == 0:
constr.basis_status = "b"
constr.basis_status = "B"
elif gp_constr.cbasis == -1:
constr.basis_status = "n"
constr.basis_status = "N"
else:
raise Exception(f"unknown cbasis: {gp_constr.cbasis}")
if self._has_lp_solution or self._has_mip_solution:
@@ -474,6 +517,26 @@ class GurobiSolver(InternalSolver):
"user_features",
]
@overrides
def get_variable_attrs(self) -> List[str]:
return [
"basis_status",
"category",
"lower_bound",
"obj_coeff",
"reduced_cost",
"sa_lb_down",
"sa_lb_up",
"sa_obj_down",
"sa_obj_up",
"sa_ub_down",
"sa_ub_up",
"type",
"upper_bound",
"user_features",
"value",
]
class GurobiTestInstanceInfeasible(Instance):
@overrides

14
miplearn/solvers/internal.py
View File

@@ -8,7 +8,7 @@ from typing import Any, Dict, List, Optional
from overrides import EnforceOverrides
from miplearn.features import Constraint
from miplearn.features import Constraint, Variable
from miplearn.instance.base import Instance
from miplearn.types import (
LPSolveStats,
@@ -247,9 +247,21 @@ class InternalSolver(ABC, EnforceOverrides):
"""
return False
@abstractmethod
def get_variables(self) -> Dict[str, Variable]:
pass
@abstractmethod
def get_constraint_attrs(self) -> List[str]:
"""
Returns a list of constraint attributes supported by this solver.
"""
pass
@abstractmethod
def get_variable_attrs(self) -> List[str]:
"""
Returns a list of variable attributes supported by this solver.
"""
pass

35
miplearn/solvers/pyomo/base.py
View File

@@ -19,6 +19,7 @@ from pyomo.core.expr.numeric_expr import SumExpression, MonomialTermExpression
from pyomo.opt import TerminationCondition
from pyomo.opt.base.solvers import SolverFactory
from miplearn.features import Variable
from miplearn.instance.base import Instance
from miplearn.solvers import _RedirectOutput
from miplearn.solvers.internal import (
@@ -363,6 +364,19 @@ class BasePyomoSolver(InternalSolver):
capacity=67.0,
)
@overrides
def get_variables(self) -> Dict[str, Variable]:
assert self.model is not None
variables = {}
for var in self.model.component_objects(pyomo.core.Var):
for idx in var:
varname = f"{var}[{idx}]"
variables[varname] = self._parse_pyomo_variable(var[idx])
return variables
def _parse_pyomo_variable(self, var: pyomo.core.Var) -> Variable:
return Variable()
@overrides
def get_constraints(self) -> Dict[str, Constraint]:
assert self.model is not None
@@ -385,6 +399,7 @@ class BasePyomoSolver(InternalSolver):
self,
pyomo_constr: pyomo.core.Constraint,
) -> Constraint:
assert self.model is not None
constr = Constraint()
# Extract RHS and sense
@@ -448,6 +463,26 @@ class BasePyomoSolver(InternalSolver):
"user_features",
]
@overrides
def get_variable_attrs(self) -> List[str]:
return [
# "basis_status",
# "category",
# "lower_bound",
# "obj_coeff",
# "reduced_cost",
# "sa_lb_down",
# "sa_lb_up",
# "sa_obj_down",
# "sa_obj_up",
# "sa_ub_down",
# "sa_ub_up",
# "type",
# "upper_bound",
# "user_features",
# "value",
]
class PyomoTestInstanceInfeasible(Instance):
@overrides

203
miplearn/solvers/tests/__init__.py
View File

@@ -4,9 +4,10 @@
from typing import Any, Dict
from miplearn.features import Constraint
from miplearn.features import Constraint, Variable
from miplearn.solvers.internal import InternalSolver
inf = float("inf")
# NOTE:
# This file is in the main source folder, so that it can be called from Julia.
@@ -20,10 +21,30 @@ def _round_constraints(constraints: Dict[str, Constraint]) -> Dict[str, Constrai
return constraints
def _round_variables(vars: Dict[str, Variable]) -> Dict[str, Variable]:
for (cname, c) in vars.items():
for attr in [
"upper_bound",
"lower_bound",
"obj_coeff",
"value",
"reduced_cost",
"sa_obj_up",
"sa_obj_down",
"sa_ub_up",
"sa_ub_down",
"sa_lb_up",
"sa_lb_down",
]:
if getattr(c, attr) is not None:
setattr(c, attr, round(getattr(c, attr), 6))
return vars
def _remove_unsupported_constr_attrs(
solver: InternalSolver,
constraints: Dict[str, Constraint],
):
) -> Dict[str, Constraint]:
for (cname, c) in constraints.items():
to_remove = []
for k in c.__dict__.keys():
@@ -34,6 +55,20 @@ def _remove_unsupported_constr_attrs(
return constraints
def _remove_unsupported_var_attrs(
solver: InternalSolver,
variables: Dict[str, Variable],
) -> Dict[str, Variable]:
for (cname, c) in variables.items():
to_remove = []
for k in c.__dict__.keys():
if k not in solver.get_variable_attrs():
to_remove.append(k)
for k in to_remove:
setattr(c, k, None)
return variables
def run_internal_solver_tests(solver: InternalSolver) -> None:
run_basic_usage_tests(solver.clone())
run_warm_start_tests(solver.clone())
@@ -51,8 +86,36 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
# Fetch variables (after-load)
assert_equals(
solver.get_variable_names(),
["x[0]", "x[1]", "x[2]", "x[3]"],
_round_variables(solver.get_variables()),
_remove_unsupported_var_attrs(
solver,
{
"x[0]": Variable(
lower_bound=0.0,
obj_coeff=505.0,
type="B",
upper_bound=1.0,
),
"x[1]": Variable(
lower_bound=0.0,
obj_coeff=352.0,
type="B",
upper_bound=1.0,
),
"x[2]": Variable(
lower_bound=0.0,
obj_coeff=458.0,
type="B",
upper_bound=1.0,
),
"x[3]": Variable(
lower_bound=0.0,
obj_coeff=220.0,
type="B",
upper_bound=1.0,
),
},
),
)
# Fetch constraints (after-load)
@@ -75,17 +138,75 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
assert_equals(round(lp_stats["LP value"], 3), 1287.923)
assert len(lp_stats["LP log"]) > 100
# Fetch variables (after-lp)
solution = solver.get_solution()
assert solution is not None
assert solution["x[0]"] is not None
assert solution["x[1]"] is not None
assert solution["x[2]"] is not None
assert solution["x[3]"] is not None
assert_equals(round(solution["x[0]"], 3), 1.000)
assert_equals(round(solution["x[1]"], 3), 0.923)
assert_equals(round(solution["x[2]"], 3), 1.000)
assert_equals(round(solution["x[3]"], 3), 0.000)
# Fetch variables (after-load)
assert_equals(
_round_variables(solver.get_variables()),
_remove_unsupported_var_attrs(
solver,
{
"x[0]": Variable(
basis_status="U",
lower_bound=0.0,
obj_coeff=505.0,
reduced_cost=193.615385,
sa_lb_down=-inf,
sa_lb_up=1.0,
sa_obj_down=311.384615,
sa_obj_up=inf,
sa_ub_down=0.913043,
sa_ub_up=2.043478,
type="C",
upper_bound=1.0,
value=1.0,
),
"x[1]": Variable(
basis_status="B",
lower_bound=0.0,
obj_coeff=352.0,
reduced_cost=0.0,
sa_lb_down=-inf,
sa_lb_up=0.923077,
sa_obj_down=317.777778,
sa_obj_up=570.869565,
sa_ub_down=0.923077,
sa_ub_up=inf,
type="C",
upper_bound=1.0,
value=0.923077,
),
"x[2]": Variable(
basis_status="U",
lower_bound=0.0,
obj_coeff=458.0,
reduced_cost=187.230769,
sa_lb_down=-inf,
sa_lb_up=1.0,
sa_obj_down=270.769231,
sa_obj_up=inf,
sa_ub_down=0.9,
sa_ub_up=2.2,
type="C",
upper_bound=1.0,
value=1.0,
),
"x[3]": Variable(
basis_status="L",
lower_bound=0.0,
obj_coeff=220.0,
reduced_cost=-23.692308,
sa_lb_down=-0.111111,
sa_lb_up=1.0,
sa_obj_down=-inf,
sa_obj_up=243.692308,
sa_ub_down=0.0,
sa_ub_up=inf,
type="C",
upper_bound=1.0,
value=0.0,
),
},
),
)
# Fetch constraints (after-lp)
assert_equals(
@@ -100,9 +221,9 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
sense="<",
slack=0.0,
dual_value=13.538462,
sa_rhs_down=None,
sa_rhs_down=43.0,
sa_rhs_up=69.0,
basis_status="n",
basis_status="N",
)
},
),
@@ -122,17 +243,43 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
assert_equals(mip_stats["Sense"], "max")
assert isinstance(mip_stats["Wallclock time"], float)
# Fetch variables (after-mip)
solution = solver.get_solution()
assert solution is not None
assert solution["x[0]"] is not None
assert solution["x[1]"] is not None
assert solution["x[2]"] is not None
assert solution["x[3]"] is not None
assert_equals(solution["x[0]"], 1.0)
assert_equals(solution["x[1]"], 0.0)
assert_equals(solution["x[2]"], 1.0)
assert_equals(solution["x[3]"], 1.0)
# Fetch variables (after-load)
assert_equals(
_round_variables(solver.get_variables()),
_remove_unsupported_var_attrs(
solver,
{
"x[0]": Variable(
lower_bound=0.0,
obj_coeff=505.0,
type="B",
upper_bound=1.0,
value=1.0,
),
"x[1]": Variable(
lower_bound=0.0,
obj_coeff=352.0,
type="B",
upper_bound=1.0,
value=0.0,
),
"x[2]": Variable(
lower_bound=0.0,
obj_coeff=458.0,
type="B",
upper_bound=1.0,
value=1.0,
),
"x[3]": Variable(
lower_bound=0.0,
obj_coeff=220.0,
type="B",
upper_bound=1.0,
value=1.0,
),
},
),
)
# Fetch constraints (after-mip)
assert_equals(