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92 lines
3.2 KiB
92 lines
3.2 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
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# Released under the modified BSD license. See COPYING.md for more details.
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from miplearn.features import (
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FeaturesExtractor,
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InstanceFeatures,
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Constraint,
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VariableFeatures,
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)
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from miplearn.solvers.gurobi import GurobiSolver
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from miplearn.solvers.tests import (
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assert_equals,
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_round_constraints,
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_round,
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)
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inf = float("inf")
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def test_knapsack() -> None:
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solver = GurobiSolver()
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instance = solver.build_test_instance_knapsack()
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model = instance.to_model()
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solver.set_instance(instance, model)
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solver.solve_lp()
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features = FeaturesExtractor(solver).extract(instance)
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assert features.variables is not None
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assert features.constraints is not None
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assert features.instance is not None
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assert_equals(
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_round(features.variables),
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VariableFeatures(
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names=("x[0]", "x[1]", "x[2]", "x[3]", "z"),
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basis_status=("U", "B", "U", "L", "U"),
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categories=("default", "default", "default", "default", None),
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lower_bounds=(0.0, 0.0, 0.0, 0.0, 0.0),
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obj_coeffs=(505.0, 352.0, 458.0, 220.0, 0.0),
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reduced_costs=(193.615385, 0.0, 187.230769, -23.692308, 13.538462),
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sa_lb_down=(-inf, -inf, -inf, -0.111111, -inf),
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sa_lb_up=(1.0, 0.923077, 1.0, 1.0, 67.0),
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sa_obj_down=(311.384615, 317.777778, 270.769231, -inf, -13.538462),
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sa_obj_up=(inf, 570.869565, inf, 243.692308, inf),
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sa_ub_down=(0.913043, 0.923077, 0.9, 0.0, 43.0),
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sa_ub_up=(2.043478, inf, 2.2, inf, 69.0),
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types=("B", "B", "B", "B", "C"),
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upper_bounds=(1.0, 1.0, 1.0, 1.0, 67.0),
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user_features=(
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(23.0, 505.0),
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(26.0, 352.0),
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(20.0, 458.0),
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(18.0, 220.0),
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None,
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),
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values=(1.0, 0.923077, 1.0, 0.0, 67.0),
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alvarez_2017=[
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[1.0, 0.32899, 0.0, 0.0, 1.0, 1.0, 5.265874, 46.051702],
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[1.0, 0.229316, 0.0, 0.076923, 1.0, 1.0, 3.532875, 5.388476],
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[1.0, 0.298371, 0.0, 0.0, 1.0, 1.0, 5.232342, 46.051702],
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[1.0, 0.143322, 0.0, 0.0, 1.0, -1.0, 46.051702, 3.16515],
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[0.0, 0.0, 0.0, 0.0, 1.0, -1.0, 0.0, 0.0],
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],
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),
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)
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assert_equals(
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_round_constraints(features.constraints),
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{
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"eq_capacity": Constraint(
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basis_status="N",
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category="eq_capacity",
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dual_value=13.538462,
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lazy=False,
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lhs={"x[0]": 23.0, "x[1]": 26.0, "x[2]": 20.0, "x[3]": 18.0, "z": -1.0},
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rhs=0.0,
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sa_rhs_down=-24.0,
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sa_rhs_up=1.9999999999999987,
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sense="=",
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slack=0.0,
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user_features=[0.0],
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)
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},
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)
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assert_equals(
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features.instance,
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InstanceFeatures(
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user_features=[67.0, 21.75],
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lazy_constraint_count=0,
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),
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)
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