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49 lines
1.6 KiB
49 lines
1.6 KiB
# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
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# Copyright (C) 2020, 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 .component import Component
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from ..extractors import *
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from abc import ABC, abstractmethod
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from copy import deepcopy
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import numpy as np
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from sklearn.pipeline import make_pipeline
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from sklearn.linear_model import LogisticRegression
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from sklearn.preprocessing import StandardScaler
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from sklearn.model_selection import cross_val_score
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from sklearn.metrics import roc_curve
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from sklearn.neighbors import KNeighborsClassifier
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from tqdm.auto import tqdm
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import pyomo.environ as pe
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import logging
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logger = logging.getLogger(__name__)
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class LazyConstraintsComponent(Component):
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"""
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A component that predicts which lazy constraints to enforce.
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"""
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def __init__(self):
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self.violations = set()
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def before_solve(self, solver, instance, model):
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logger.info("Enforcing %d lazy constraints" % len(self.violations))
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for v in self.violations:
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cut = instance.build_lazy_constraint(model, v)
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solver.internal_solver.add_constraint(cut)
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def after_solve(self, solver, instance, model):
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pass
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def fit(self, training_instances):
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for instance in training_instances:
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if not hasattr(instance, "found_violations"):
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continue
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for v in instance.found_violations:
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self.violations.add(v)
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def predict(self, instance, model=None):
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return self.violations
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