# MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization # Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved. # Released under the modified BSD license. See COPYING.md for more details. import logging from typing import Optional, List, Dict from overrides import overrides from pyomo import environ as pe from scipy.stats import randint from miplearn.features import Variable from miplearn.solvers.gurobi import GurobiSolver from miplearn.solvers.pyomo.base import BasePyomoSolver from miplearn.types import SolverParams, BranchPriorities logger = logging.getLogger(__name__) class GurobiPyomoSolver(BasePyomoSolver): """ An InternalSolver that uses Gurobi and the Pyomo modeling language. Parameters ---------- params: dict Dictionary of options to pass to the Pyomo solver. For example, {"Threads": 4} to set the number of threads. """ def __init__( self, params: Optional[SolverParams] = None, ) -> None: if params is None: params = {} params["seed"] = randint(low=0, high=1000).rvs() super().__init__( solver_factory=pe.SolverFactory("gurobi_persistent"), params=params, ) @overrides def clone(self) -> "GurobiPyomoSolver": return GurobiPyomoSolver(params=self.params) @overrides def set_branching_priorities(self, priorities: BranchPriorities) -> None: from gurobipy import GRB for (varname, priority) in priorities.items(): if priority is None: continue var = self._varname_to_var[varname] gvar = self._pyomo_solver._pyomo_var_to_solver_var_map[var] gvar.setAttr(GRB.Attr.BranchPriority, int(round(priority))) @overrides def _extract_node_count(self, log: str) -> int: return max(1, int(self._pyomo_solver._solver_model.getAttr("NodeCount"))) @overrides def _get_warm_start_regexp(self) -> str: return "MIP start with objective ([0-9.e+-]*)" @overrides def _get_node_count_regexp(self) -> Optional[str]: return None