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44 lines
1.3 KiB
44 lines
1.3 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 typing import Optional
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from pyomo import environ as pe
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from scipy.stats import randint
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from miplearn.solvers.pyomo.base import BasePyomoSolver
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from miplearn.types import SolverParams
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class CplexPyomoSolver(BasePyomoSolver):
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"""
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An InternalSolver that uses CPLEX and the Pyomo modeling language.
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Parameters
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----------
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params: dict
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Dictionary of options to pass to the Pyomo solver. For example,
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{"mip_display": 5} to increase the log verbosity.
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"""
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def __init__(
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self,
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params: Optional[SolverParams] = None,
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) -> None:
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if params is None:
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params = {}
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if "randomseed" not in params.keys():
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params["randomseed"] = randint(low=0, high=1000).rvs()
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if "mip_display" not in params.keys():
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params["mip_display"] = 4
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super().__init__(
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solver_factory=pe.SolverFactory("cplex_persistent"),
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params=params,
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)
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def _get_warm_start_regexp(self):
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return "MIP start .* with objective ([0-9.e+-]*)\\."
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def _get_node_count_regexp(self):
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return "^[ *] *([0-9]+)"
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