You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
30 lines
1.0 KiB
30 lines
1.0 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
|
|
# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
|
|
# Released under the modified BSD license. See COPYING.md for more details.
|
|
|
|
from miplearn import ObjectiveValueComponent, LearningSolver
|
|
from miplearn.problems.knapsack import KnapsackInstance
|
|
|
|
def _get_instances():
|
|
instances = [
|
|
KnapsackInstance(
|
|
weights=[23., 26., 20., 18.],
|
|
prices=[505., 352., 458., 220.],
|
|
capacity=67.,
|
|
),
|
|
]
|
|
models = [instance.to_model() for instance in instances]
|
|
solver = LearningSolver()
|
|
for i in range(len(instances)):
|
|
solver.solve(instances[i], models[i])
|
|
return instances, models
|
|
|
|
|
|
def test_usage():
|
|
instances, models = _get_instances()
|
|
comp = ObjectiveValueComponent()
|
|
comp.fit(instances)
|
|
assert instances[0].lower_bound == 1183.0
|
|
assert instances[0].upper_bound == 1183.0
|
|
assert comp.predict(instances).tolist() == [[1183.0, 1183.0]]
|