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38 lines
1.3 KiB
38 lines
1.3 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 pyomo import environ as pe
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from scipy.stats import randint
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from .base import BasePyomoSolver
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class CplexPyomoSolver(BasePyomoSolver):
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def __init__(self, options=None):
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"""
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Creates a new CPLEX solver, accessed through Pyomo.
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Parameters
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----------
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options: 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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super().__init__()
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self._pyomo_solver = pe.SolverFactory("cplex_persistent")
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self._pyomo_solver.options["randomseed"] = randint(low=0, high=1000).rvs()
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self._pyomo_solver.options["mip_display"] = 4
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if options is not None:
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for (key, value) in options.items():
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self._pyomo_solver.options[key] = value
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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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def set_branching_priorities(self, priorities):
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raise NotImplementedError
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