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<body>
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<main>
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<article id="content">
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<header>
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<h1 class="title">Module <code>miplearn.solvers.pyomo.base</code></h1>
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</header>
|
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<section id="section-intro">
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<details class="source">
|
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<summary>
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<span>Expand source code</span>
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</summary>
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<pre><code class="python"># 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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import logging
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import re
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import sys
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from io import StringIO
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from typing import Any, List, Dict, Optional
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import pyomo
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from pyomo import environ as pe
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from pyomo.core import Var, Constraint
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from pyomo.opt import TerminationCondition
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from pyomo.opt.base.solvers import SolverFactory
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from miplearn.instance import Instance
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from miplearn.solvers import _RedirectOutput
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from miplearn.solvers.internal import (
|
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InternalSolver,
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LPSolveStats,
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IterationCallback,
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LazyCallback,
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MIPSolveStats,
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)
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from miplearn.types import VarIndex, SolverParams, Solution
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logger = logging.getLogger(__name__)
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class BasePyomoSolver(InternalSolver):
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"""
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Base class for all Pyomo solvers.
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"""
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def __init__(
|
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self,
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solver_factory: SolverFactory,
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params: SolverParams,
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) -> None:
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self.instance: Optional[Instance] = None
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self.model: Optional[pe.ConcreteModel] = None
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self._all_vars: List[pe.Var] = []
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self._bin_vars: List[pe.Var] = []
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self._is_warm_start_available: bool = False
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self._pyomo_solver: SolverFactory = solver_factory
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self._obj_sense: str = "min"
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self._varname_to_var: Dict[str, pe.Var] = {}
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self._cname_to_constr: Dict[str, pe.Constraint] = {}
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self._termination_condition: str = ""
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for (key, value) in params.items():
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self._pyomo_solver.options[key] = value
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def solve_lp(
|
||||
self,
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tee: bool = False,
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) -> LPSolveStats:
|
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self.relax()
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streams: List[Any] = [StringIO()]
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if tee:
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streams += [sys.stdout]
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with _RedirectOutput(streams):
|
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results = self._pyomo_solver.solve(tee=True)
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self._restore_integrality()
|
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opt_value = None
|
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if not self.is_infeasible():
|
||||
opt_value = results["Problem"][0]["Lower bound"]
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||||
return {
|
||||
"Optimal value": opt_value,
|
||||
"Log": streams[0].getvalue(),
|
||||
}
|
||||
|
||||
def _restore_integrality(self) -> None:
|
||||
for var in self._bin_vars:
|
||||
var.domain = pyomo.core.base.set_types.Binary
|
||||
self._pyomo_solver.update_var(var)
|
||||
|
||||
def solve(
|
||||
self,
|
||||
tee: bool = False,
|
||||
iteration_cb: IterationCallback = None,
|
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lazy_cb: LazyCallback = None,
|
||||
) -> MIPSolveStats:
|
||||
if lazy_cb is not None:
|
||||
raise Exception("lazy callback not supported")
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total_wallclock_time = 0
|
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streams: List[Any] = [StringIO()]
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||||
if tee:
|
||||
streams += [sys.stdout]
|
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if iteration_cb is None:
|
||||
iteration_cb = lambda: False
|
||||
while True:
|
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logger.debug("Solving MIP...")
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with _RedirectOutput(streams):
|
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results = self._pyomo_solver.solve(
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tee=True,
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warmstart=self._is_warm_start_available,
|
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)
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total_wallclock_time += results["Solver"][0]["Wallclock time"]
|
||||
should_repeat = iteration_cb()
|
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if not should_repeat:
|
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break
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log = streams[0].getvalue()
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node_count = self._extract_node_count(log)
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ws_value = self._extract_warm_start_value(log)
|
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self._termination_condition = results["Solver"][0]["Termination condition"]
|
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lb, ub = None, None
|
||||
if not self.is_infeasible():
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lb = results["Problem"][0]["Lower bound"]
|
||||
ub = results["Problem"][0]["Upper bound"]
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||||
stats: MIPSolveStats = {
|
||||
"Lower bound": lb,
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"Upper bound": ub,
|
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"Wallclock time": total_wallclock_time,
|
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"Sense": self._obj_sense,
|
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"Log": log,
|
||||
"Nodes": node_count,
|
||||
"Warm start value": ws_value,
|
||||
"LP value": None,
|
||||
}
|
||||
return stats
|
||||
|
||||
def get_solution(self) -> Optional[Solution]:
|
||||
assert self.model is not None
|
||||
if self.is_infeasible():
|
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return None
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solution: Solution = {}
|
||||
for var in self.model.component_objects(Var):
|
||||
solution[str(var)] = {}
|
||||
for index in var:
|
||||
if var[index].fixed:
|
||||
continue
|
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solution[str(var)][index] = var[index].value
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return solution
|
||||
|
||||
def set_warm_start(self, solution: Solution) -> None:
|
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self._clear_warm_start()
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count_total, count_fixed = 0, 0
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for var_name in solution:
|
||||
var = self._varname_to_var[var_name]
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for index in solution[var_name]:
|
||||
count_total += 1
|
||||
var[index].value = solution[var_name][index]
|
||||
if solution[var_name][index] is not None:
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||||
count_fixed += 1
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||||
if count_fixed > 0:
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self._is_warm_start_available = True
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||||
logger.info(
|
||||
"Setting start values for %d variables (out of %d)"
|
||||
% (count_fixed, count_total)
|
||||
)
|
||||
|
||||
def set_instance(
|
||||
self,
|
||||
instance: Instance,
|
||||
model: Any = None,
|
||||
) -> None:
|
||||
if model is None:
|
||||
model = instance.to_model()
|
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assert isinstance(model, pe.ConcreteModel)
|
||||
self.instance = instance
|
||||
self.model = model
|
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self._pyomo_solver.set_instance(model)
|
||||
self._update_obj()
|
||||
self._update_vars()
|
||||
self._update_constrs()
|
||||
|
||||
def get_value(self, var_name: str, index: VarIndex) -> Optional[float]:
|
||||
if self.is_infeasible():
|
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return None
|
||||
else:
|
||||
var = self._varname_to_var[var_name]
|
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return var[index].value
|
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|
||||
def get_empty_solution(self) -> Solution:
|
||||
assert self.model is not None
|
||||
solution: Solution = {}
|
||||
for var in self.model.component_objects(Var):
|
||||
svar = str(var)
|
||||
solution[svar] = {}
|
||||
for index in var:
|
||||
if var[index].fixed:
|
||||
continue
|
||||
solution[svar][index] = None
|
||||
return solution
|
||||
|
||||
def _clear_warm_start(self) -> None:
|
||||
for var in self._all_vars:
|
||||
if not var.fixed:
|
||||
var.value = None
|
||||
self._is_warm_start_available = False
|
||||
|
||||
def _update_obj(self) -> None:
|
||||
self._obj_sense = "max"
|
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if self._pyomo_solver._objective.sense == pyomo.core.kernel.objective.minimize:
|
||||
self._obj_sense = "min"
|
||||
|
||||
def _update_vars(self) -> None:
|
||||
assert self.model is not None
|
||||
self._all_vars = []
|
||||
self._bin_vars = []
|
||||
self._varname_to_var = {}
|
||||
for var in self.model.component_objects(Var):
|
||||
self._varname_to_var[var.name] = var
|
||||
for idx in var:
|
||||
self._all_vars += [var[idx]]
|
||||
if var[idx].domain == pyomo.core.base.set_types.Binary:
|
||||
self._bin_vars += [var[idx]]
|
||||
|
||||
def _update_constrs(self) -> None:
|
||||
assert self.model is not None
|
||||
self._cname_to_constr = {}
|
||||
for constr in self.model.component_objects(Constraint):
|
||||
self._cname_to_constr[constr.name] = constr
|
||||
|
||||
def fix(self, solution):
|
||||
count_total, count_fixed = 0, 0
|
||||
for varname in solution:
|
||||
for index in solution[varname]:
|
||||
var = self._varname_to_var[varname]
|
||||
count_total += 1
|
||||
if solution[varname][index] is None:
|
||||
continue
|
||||
count_fixed += 1
|
||||
var[index].fix(solution[varname][index])
|
||||
self._pyomo_solver.update_var(var[index])
|
||||
logger.info(
|
||||
"Fixing values for %d variables (out of %d)"
|
||||
% (
|
||||
count_fixed,
|
||||
count_total,
|
||||
)
|
||||
)
|
||||
|
||||
def add_constraint(self, constraint):
|
||||
self._pyomo_solver.add_constraint(constraint)
|
||||
self._update_constrs()
|
||||
|
||||
@staticmethod
|
||||
def __extract(
|
||||
log: str,
|
||||
regexp: Optional[str],
|
||||
default: Optional[str] = None,
|
||||
) -> Optional[str]:
|
||||
if regexp is None:
|
||||
return default
|
||||
value = default
|
||||
for line in log.splitlines():
|
||||
matches = re.findall(regexp, line)
|
||||
if len(matches) == 0:
|
||||
continue
|
||||
value = matches[0]
|
||||
return value
|
||||
|
||||
def _extract_warm_start_value(self, log: str) -> Optional[float]:
|
||||
value = self.__extract(log, self._get_warm_start_regexp())
|
||||
if value is None:
|
||||
return None
|
||||
return float(value)
|
||||
|
||||
def _extract_node_count(self, log: str) -> Optional[int]:
|
||||
value = self.__extract(log, self._get_node_count_regexp())
|
||||
if value is None:
|
||||
return None
|
||||
return int(value)
|
||||
|
||||
def get_constraint_ids(self):
|
||||
return list(self._cname_to_constr.keys())
|
||||
|
||||
def _get_warm_start_regexp(self) -> Optional[str]:
|
||||
return None
|
||||
|
||||
def _get_node_count_regexp(self) -> Optional[str]:
|
||||
return None
|
||||
|
||||
def relax(self) -> None:
|
||||
for var in self._bin_vars:
|
||||
lb, ub = var.bounds
|
||||
var.setlb(lb)
|
||||
var.setub(ub)
|
||||
var.domain = pyomo.core.base.set_types.Reals
|
||||
self._pyomo_solver.update_var(var)
|
||||
|
||||
def get_inequality_slacks(self) -> Dict[str, float]:
|
||||
result: Dict[str, float] = {}
|
||||
for (cname, cobj) in self._cname_to_constr.items():
|
||||
if cobj.equality:
|
||||
continue
|
||||
result[cname] = cobj.slack()
|
||||
return result
|
||||
|
||||
def get_constraint_sense(self, cid: str) -> str:
|
||||
cobj = self._cname_to_constr[cid]
|
||||
has_ub = cobj.has_ub()
|
||||
has_lb = cobj.has_lb()
|
||||
assert (not has_lb) or (not has_ub), "range constraints not supported"
|
||||
if has_lb:
|
||||
return ">"
|
||||
elif has_ub:
|
||||
return "<"
|
||||
else:
|
||||
return "="
|
||||
|
||||
def set_constraint_sense(self, cid: str, sense: str) -> None:
|
||||
raise Exception("Not implemented")
|
||||
|
||||
def extract_constraint(self, cid: str) -> Constraint:
|
||||
raise Exception("Not implemented")
|
||||
|
||||
def is_constraint_satisfied(self, cobj: Constraint) -> bool:
|
||||
raise Exception("Not implemented")
|
||||
|
||||
def is_infeasible(self) -> bool:
|
||||
return self._termination_condition == TerminationCondition.infeasible
|
||||
|
||||
def get_dual(self, cid):
|
||||
raise Exception("Not implemented")
|
||||
|
||||
def get_sense(self) -> str:
|
||||
return self._obj_sense</code></pre>
|
||||
</details>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
<h2 class="section-title" id="header-classes">Classes</h2>
|
||||
<dl>
|
||||
<dt id="miplearn.solvers.pyomo.base.BasePyomoSolver"><code class="flex name class">
|
||||
<span>class <span class="ident">BasePyomoSolver</span></span>
|
||||
<span>(</span><span>solver_factory, params)</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<section class="desc"><p>Base class for all Pyomo solvers.</p></section>
|
||||
<details class="source">
|
||||
<summary>
|
||||
<span>Expand source code</span>
|
||||
</summary>
|
||||
<pre><code class="python">class BasePyomoSolver(InternalSolver):
|
||||
"""
|
||||
Base class for all Pyomo solvers.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
solver_factory: SolverFactory,
|
||||
params: SolverParams,
|
||||
) -> None:
|
||||
self.instance: Optional[Instance] = None
|
||||
self.model: Optional[pe.ConcreteModel] = None
|
||||
self._all_vars: List[pe.Var] = []
|
||||
self._bin_vars: List[pe.Var] = []
|
||||
self._is_warm_start_available: bool = False
|
||||
self._pyomo_solver: SolverFactory = solver_factory
|
||||
self._obj_sense: str = "min"
|
||||
self._varname_to_var: Dict[str, pe.Var] = {}
|
||||
self._cname_to_constr: Dict[str, pe.Constraint] = {}
|
||||
self._termination_condition: str = ""
|
||||
|
||||
for (key, value) in params.items():
|
||||
self._pyomo_solver.options[key] = value
|
||||
|
||||
def solve_lp(
|
||||
self,
|
||||
tee: bool = False,
|
||||
) -> LPSolveStats:
|
||||
self.relax()
|
||||
streams: List[Any] = [StringIO()]
|
||||
if tee:
|
||||
streams += [sys.stdout]
|
||||
with _RedirectOutput(streams):
|
||||
results = self._pyomo_solver.solve(tee=True)
|
||||
self._restore_integrality()
|
||||
opt_value = None
|
||||
if not self.is_infeasible():
|
||||
opt_value = results["Problem"][0]["Lower bound"]
|
||||
return {
|
||||
"Optimal value": opt_value,
|
||||
"Log": streams[0].getvalue(),
|
||||
}
|
||||
|
||||
def _restore_integrality(self) -> None:
|
||||
for var in self._bin_vars:
|
||||
var.domain = pyomo.core.base.set_types.Binary
|
||||
self._pyomo_solver.update_var(var)
|
||||
|
||||
def solve(
|
||||
self,
|
||||
tee: bool = False,
|
||||
iteration_cb: IterationCallback = None,
|
||||
lazy_cb: LazyCallback = None,
|
||||
) -> MIPSolveStats:
|
||||
if lazy_cb is not None:
|
||||
raise Exception("lazy callback not supported")
|
||||
total_wallclock_time = 0
|
||||
streams: List[Any] = [StringIO()]
|
||||
if tee:
|
||||
streams += [sys.stdout]
|
||||
if iteration_cb is None:
|
||||
iteration_cb = lambda: False
|
||||
while True:
|
||||
logger.debug("Solving MIP...")
|
||||
with _RedirectOutput(streams):
|
||||
results = self._pyomo_solver.solve(
|
||||
tee=True,
|
||||
warmstart=self._is_warm_start_available,
|
||||
)
|
||||
total_wallclock_time += results["Solver"][0]["Wallclock time"]
|
||||
should_repeat = iteration_cb()
|
||||
if not should_repeat:
|
||||
break
|
||||
log = streams[0].getvalue()
|
||||
node_count = self._extract_node_count(log)
|
||||
ws_value = self._extract_warm_start_value(log)
|
||||
self._termination_condition = results["Solver"][0]["Termination condition"]
|
||||
lb, ub = None, None
|
||||
if not self.is_infeasible():
|
||||
lb = results["Problem"][0]["Lower bound"]
|
||||
ub = results["Problem"][0]["Upper bound"]
|
||||
stats: MIPSolveStats = {
|
||||
"Lower bound": lb,
|
||||
"Upper bound": ub,
|
||||
"Wallclock time": total_wallclock_time,
|
||||
"Sense": self._obj_sense,
|
||||
"Log": log,
|
||||
"Nodes": node_count,
|
||||
"Warm start value": ws_value,
|
||||
"LP value": None,
|
||||
}
|
||||
return stats
|
||||
|
||||
def get_solution(self) -> Optional[Solution]:
|
||||
assert self.model is not None
|
||||
if self.is_infeasible():
|
||||
return None
|
||||
solution: Solution = {}
|
||||
for var in self.model.component_objects(Var):
|
||||
solution[str(var)] = {}
|
||||
for index in var:
|
||||
if var[index].fixed:
|
||||
continue
|
||||
solution[str(var)][index] = var[index].value
|
||||
return solution
|
||||
|
||||
def set_warm_start(self, solution: Solution) -> None:
|
||||
self._clear_warm_start()
|
||||
count_total, count_fixed = 0, 0
|
||||
for var_name in solution:
|
||||
var = self._varname_to_var[var_name]
|
||||
for index in solution[var_name]:
|
||||
count_total += 1
|
||||
var[index].value = solution[var_name][index]
|
||||
if solution[var_name][index] is not None:
|
||||
count_fixed += 1
|
||||
if count_fixed > 0:
|
||||
self._is_warm_start_available = True
|
||||
logger.info(
|
||||
"Setting start values for %d variables (out of %d)"
|
||||
% (count_fixed, count_total)
|
||||
)
|
||||
|
||||
def set_instance(
|
||||
self,
|
||||
instance: Instance,
|
||||
model: Any = None,
|
||||
) -> None:
|
||||
if model is None:
|
||||
model = instance.to_model()
|
||||
assert isinstance(model, pe.ConcreteModel)
|
||||
self.instance = instance
|
||||
self.model = model
|
||||
self._pyomo_solver.set_instance(model)
|
||||
self._update_obj()
|
||||
self._update_vars()
|
||||
self._update_constrs()
|
||||
|
||||
def get_value(self, var_name: str, index: VarIndex) -> Optional[float]:
|
||||
if self.is_infeasible():
|
||||
return None
|
||||
else:
|
||||
var = self._varname_to_var[var_name]
|
||||
return var[index].value
|
||||
|
||||
def get_empty_solution(self) -> Solution:
|
||||
assert self.model is not None
|
||||
solution: Solution = {}
|
||||
for var in self.model.component_objects(Var):
|
||||
svar = str(var)
|
||||
solution[svar] = {}
|
||||
for index in var:
|
||||
if var[index].fixed:
|
||||
continue
|
||||
solution[svar][index] = None
|
||||
return solution
|
||||
|
||||
def _clear_warm_start(self) -> None:
|
||||
for var in self._all_vars:
|
||||
if not var.fixed:
|
||||
var.value = None
|
||||
self._is_warm_start_available = False
|
||||
|
||||
def _update_obj(self) -> None:
|
||||
self._obj_sense = "max"
|
||||
if self._pyomo_solver._objective.sense == pyomo.core.kernel.objective.minimize:
|
||||
self._obj_sense = "min"
|
||||
|
||||
def _update_vars(self) -> None:
|
||||
assert self.model is not None
|
||||
self._all_vars = []
|
||||
self._bin_vars = []
|
||||
self._varname_to_var = {}
|
||||
for var in self.model.component_objects(Var):
|
||||
self._varname_to_var[var.name] = var
|
||||
for idx in var:
|
||||
self._all_vars += [var[idx]]
|
||||
if var[idx].domain == pyomo.core.base.set_types.Binary:
|
||||
self._bin_vars += [var[idx]]
|
||||
|
||||
def _update_constrs(self) -> None:
|
||||
assert self.model is not None
|
||||
self._cname_to_constr = {}
|
||||
for constr in self.model.component_objects(Constraint):
|
||||
self._cname_to_constr[constr.name] = constr
|
||||
|
||||
def fix(self, solution):
|
||||
count_total, count_fixed = 0, 0
|
||||
for varname in solution:
|
||||
for index in solution[varname]:
|
||||
var = self._varname_to_var[varname]
|
||||
count_total += 1
|
||||
if solution[varname][index] is None:
|
||||
continue
|
||||
count_fixed += 1
|
||||
var[index].fix(solution[varname][index])
|
||||
self._pyomo_solver.update_var(var[index])
|
||||
logger.info(
|
||||
"Fixing values for %d variables (out of %d)"
|
||||
% (
|
||||
count_fixed,
|
||||
count_total,
|
||||
)
|
||||
)
|
||||
|
||||
def add_constraint(self, constraint):
|
||||
self._pyomo_solver.add_constraint(constraint)
|
||||
self._update_constrs()
|
||||
|
||||
@staticmethod
|
||||
def __extract(
|
||||
log: str,
|
||||
regexp: Optional[str],
|
||||
default: Optional[str] = None,
|
||||
) -> Optional[str]:
|
||||
if regexp is None:
|
||||
return default
|
||||
value = default
|
||||
for line in log.splitlines():
|
||||
matches = re.findall(regexp, line)
|
||||
if len(matches) == 0:
|
||||
continue
|
||||
value = matches[0]
|
||||
return value
|
||||
|
||||
def _extract_warm_start_value(self, log: str) -> Optional[float]:
|
||||
value = self.__extract(log, self._get_warm_start_regexp())
|
||||
if value is None:
|
||||
return None
|
||||
return float(value)
|
||||
|
||||
def _extract_node_count(self, log: str) -> Optional[int]:
|
||||
value = self.__extract(log, self._get_node_count_regexp())
|
||||
if value is None:
|
||||
return None
|
||||
return int(value)
|
||||
|
||||
def get_constraint_ids(self):
|
||||
return list(self._cname_to_constr.keys())
|
||||
|
||||
def _get_warm_start_regexp(self) -> Optional[str]:
|
||||
return None
|
||||
|
||||
def _get_node_count_regexp(self) -> Optional[str]:
|
||||
return None
|
||||
|
||||
def relax(self) -> None:
|
||||
for var in self._bin_vars:
|
||||
lb, ub = var.bounds
|
||||
var.setlb(lb)
|
||||
var.setub(ub)
|
||||
var.domain = pyomo.core.base.set_types.Reals
|
||||
self._pyomo_solver.update_var(var)
|
||||
|
||||
def get_inequality_slacks(self) -> Dict[str, float]:
|
||||
result: Dict[str, float] = {}
|
||||
for (cname, cobj) in self._cname_to_constr.items():
|
||||
if cobj.equality:
|
||||
continue
|
||||
result[cname] = cobj.slack()
|
||||
return result
|
||||
|
||||
def get_constraint_sense(self, cid: str) -> str:
|
||||
cobj = self._cname_to_constr[cid]
|
||||
has_ub = cobj.has_ub()
|
||||
has_lb = cobj.has_lb()
|
||||
assert (not has_lb) or (not has_ub), "range constraints not supported"
|
||||
if has_lb:
|
||||
return ">"
|
||||
elif has_ub:
|
||||
return "<"
|
||||
else:
|
||||
return "="
|
||||
|
||||
def set_constraint_sense(self, cid: str, sense: str) -> None:
|
||||
raise Exception("Not implemented")
|
||||
|
||||
def extract_constraint(self, cid: str) -> Constraint:
|
||||
raise Exception("Not implemented")
|
||||
|
||||
def is_constraint_satisfied(self, cobj: Constraint) -> bool:
|
||||
raise Exception("Not implemented")
|
||||
|
||||
def is_infeasible(self) -> bool:
|
||||
return self._termination_condition == TerminationCondition.infeasible
|
||||
|
||||
def get_dual(self, cid):
|
||||
raise Exception("Not implemented")
|
||||
|
||||
def get_sense(self) -> str:
|
||||
return self._obj_sense</code></pre>
|
||||
</details>
|
||||
<h3>Ancestors</h3>
|
||||
<ul class="hlist">
|
||||
<li><a title="miplearn.solvers.internal.InternalSolver" href="../internal.html#miplearn.solvers.internal.InternalSolver">InternalSolver</a></li>
|
||||
<li>abc.ABC</li>
|
||||
</ul>
|
||||
<h3>Subclasses</h3>
|
||||
<ul class="hlist">
|
||||
<li><a title="miplearn.solvers.pyomo.gurobi.GurobiPyomoSolver" href="gurobi.html#miplearn.solvers.pyomo.gurobi.GurobiPyomoSolver">GurobiPyomoSolver</a></li>
|
||||
<li><a title="miplearn.solvers.pyomo.cplex.CplexPyomoSolver" href="cplex.html#miplearn.solvers.pyomo.cplex.CplexPyomoSolver">CplexPyomoSolver</a></li>
|
||||
<li><a title="miplearn.solvers.pyomo.xpress.XpressPyomoSolver" href="xpress.html#miplearn.solvers.pyomo.xpress.XpressPyomoSolver">XpressPyomoSolver</a></li>
|
||||
</ul>
|
||||
<h3>Inherited members</h3>
|
||||
<ul class="hlist">
|
||||
<li><code><b><a title="miplearn.solvers.internal.InternalSolver" href="../internal.html#miplearn.solvers.internal.InternalSolver">InternalSolver</a></b></code>:
|
||||
<ul class="hlist">
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.add_constraint" href="../internal.html#miplearn.solvers.internal.InternalSolver.add_constraint">add_constraint</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.extract_constraint" href="../internal.html#miplearn.solvers.internal.InternalSolver.extract_constraint">extract_constraint</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.fix" href="../internal.html#miplearn.solvers.internal.InternalSolver.fix">fix</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.get_constraint_ids" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_constraint_ids">get_constraint_ids</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.get_constraint_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_constraint_sense">get_constraint_sense</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.get_dual" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_dual">get_dual</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.get_empty_solution" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_empty_solution">get_empty_solution</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.get_inequality_slacks" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_inequality_slacks">get_inequality_slacks</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.get_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_sense">get_sense</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.get_solution" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_solution">get_solution</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.get_value" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_value">get_value</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.is_constraint_satisfied" href="../internal.html#miplearn.solvers.internal.InternalSolver.is_constraint_satisfied">is_constraint_satisfied</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.is_infeasible" href="../internal.html#miplearn.solvers.internal.InternalSolver.is_infeasible">is_infeasible</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.relax" href="../internal.html#miplearn.solvers.internal.InternalSolver.relax">relax</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.set_branching_priorities" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_branching_priorities">set_branching_priorities</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.set_constraint_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_constraint_sense">set_constraint_sense</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.set_instance" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_instance">set_instance</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.set_warm_start" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_warm_start">set_warm_start</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.solve" href="../internal.html#miplearn.solvers.internal.InternalSolver.solve">solve</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.internal.InternalSolver.solve_lp" href="../internal.html#miplearn.solvers.internal.InternalSolver.solve_lp">solve_lp</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</dd>
|
||||
</dl>
|
||||
</section>
|
||||
</article>
|
||||
<nav id="sidebar">
|
||||
<h1>Index</h1>
|
||||
<div class="toc">
|
||||
<ul></ul>
|
||||
</div>
|
||||
<ul id="index">
|
||||
<li><h3>Super-module</h3>
|
||||
<ul>
|
||||
<li><code><a title="miplearn.solvers.pyomo" href="index.html">miplearn.solvers.pyomo</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><h3><a href="#header-classes">Classes</a></h3>
|
||||
<ul>
|
||||
<li>
|
||||
<h4><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver" href="#miplearn.solvers.pyomo.base.BasePyomoSolver">BasePyomoSolver</a></code></h4>
|
||||
</li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</nav>
|
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</main>
|
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<footer id="footer">
|
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<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
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<script>hljs.initHighlightingOnLoad()</script>
|
||||
</body>
|
||||
</html>
|
||||
193
0.2/api/miplearn/solvers/pyomo/cplex.html
Normal file
193
0.2/api/miplearn/solvers/pyomo/cplex.html
Normal file
@@ -0,0 +1,193 @@
|
||||
<!doctype html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="utf-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1" />
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<meta name="generator" content="pdoc 0.7.0" />
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<title>miplearn.solvers.pyomo.cplex API documentation</title>
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<meta name="description" content="" />
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<link href='https://cdnjs.cloudflare.com/ajax/libs/normalize/8.0.0/normalize.min.css' rel='stylesheet'>
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|
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<style>.flex{display:flex !important}body{line-height:1.5em}#content{padding:20px}#sidebar{padding:30px;overflow:hidden}.http-server-breadcrumbs{font-size:130%;margin:0 0 15px 0}#footer{font-size:.75em;padding:5px 30px;border-top:1px solid #ddd;text-align:right}#footer p{margin:0 0 0 1em;display:inline-block}#footer p:last-child{margin-right:30px}h1,h2,h3,h4,h5{font-weight:300}h1{font-size:2.5em;line-height:1.1em}h2{font-size:1.75em;margin:1em 0 .50em 0}h3{font-size:1.4em;margin:25px 0 10px 0}h4{margin:0;font-size:105%}a{color:#058;text-decoration:none;transition:color .3s ease-in-out}a:hover{color:#e82}.title code{font-weight:bold}h2[id^="header-"]{margin-top:2em}.ident{color:#900}pre code{background:#f8f8f8;font-size:.8em;line-height:1.4em}code{background:#f2f2f1;padding:1px 4px;overflow-wrap:break-word}h1 code{background:transparent}pre{background:#f8f8f8;border:0;border-top:1px solid #ccc;border-bottom:1px solid #ccc;margin:1em 0;padding:1ex}#http-server-module-list{display:flex;flex-flow:column}#http-server-module-list div{display:flex}#http-server-module-list dt{min-width:10%}#http-server-module-list p{margin-top:0}.toc ul,#index{list-style-type:none;margin:0;padding:0}#index code{background:transparent}#index h3{border-bottom:1px solid #ddd}#index ul{padding:0}#index h4{font-weight:bold}#index h4 + ul{margin-bottom:.6em}@media (min-width:200ex){#index .two-column{column-count:2}}@media (min-width:300ex){#index .two-column{column-count:3}}dl{margin-bottom:2em}dl dl:last-child{margin-bottom:4em}dd{margin:0 0 1em 3em}#header-classes + dl > dd{margin-bottom:3em}dd dd{margin-left:2em}dd p{margin:10px 0}.name{background:#eee;font-weight:bold;font-size:.85em;padding:5px 10px;display:inline-block;min-width:40%}.name:hover{background:#e0e0e0}.name > span:first-child{white-space:nowrap}.name.class > span:nth-child(2){margin-left:.4em}.inherited{color:#999;border-left:5px solid #eee;padding-left:1em}.inheritance em{font-style:normal;font-weight:bold}.desc h2{font-weight:400;font-size:1.25em}.desc h3{font-size:1em}.desc dt code{background:inherit}.source summary,.git-link-div{color:#666;text-align:right;font-weight:400;font-size:.8em;text-transform:uppercase}.source summary > *{white-space:nowrap;cursor:pointer}.git-link{color:inherit;margin-left:1em}.source pre{max-height:500px;overflow:auto;margin:0}.source pre code{font-size:12px;overflow:visible}.hlist{list-style:none}.hlist li{display:inline}.hlist li:after{content:',\2002'}.hlist li:last-child:after{content:none}.hlist .hlist{display:inline;padding-left:1em}img{max-width:100%}.admonition{padding:.1em .5em;margin-bottom:1em}.admonition-title{font-weight:bold}.admonition.note,.admonition.info,.admonition.important{background:#aef}.admonition.todo,.admonition.versionadded,.admonition.tip,.admonition.hint{background:#dfd}.admonition.warning,.admonition.versionchanged,.admonition.deprecated{background:#fd4}.admonition.error,.admonition.danger,.admonition.caution{background:lightpink}</style>
|
||||
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|
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<style media="print">@media print{#sidebar h1{page-break-before:always}.source{display:none}}@media print{*{background:transparent !important;color:#000 !important;box-shadow:none !important;text-shadow:none !important}a[href]:after{content:" (" attr(href) ")";font-size:90%}a[href][title]:after{content:none}abbr[title]:after{content:" (" attr(title) ")"}.ir a:after,a[href^="javascript:"]:after,a[href^="#"]:after{content:""}pre,blockquote{border:1px solid #999;page-break-inside:avoid}thead{display:table-header-group}tr,img{page-break-inside:avoid}img{max-width:100% !important}@page{margin:0.5cm}p,h2,h3{orphans:3;widows:3}h1,h2,h3,h4,h5,h6{page-break-after:avoid}}</style>
|
||||
</head>
|
||||
<body>
|
||||
<main>
|
||||
<article id="content">
|
||||
<header>
|
||||
<h1 class="title">Module <code>miplearn.solvers.pyomo.cplex</code></h1>
|
||||
</header>
|
||||
<section id="section-intro">
|
||||
<details class="source">
|
||||
<summary>
|
||||
<span>Expand source code</span>
|
||||
</summary>
|
||||
<pre><code class="python"># 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 typing import Optional
|
||||
|
||||
from pyomo import environ as pe
|
||||
from scipy.stats import randint
|
||||
|
||||
from miplearn.solvers.pyomo.base import BasePyomoSolver
|
||||
from miplearn.types import SolverParams
|
||||
|
||||
|
||||
class CplexPyomoSolver(BasePyomoSolver):
|
||||
"""
|
||||
An InternalSolver that uses CPLEX and the Pyomo modeling language.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
params: dict
|
||||
Dictionary of options to pass to the Pyomo solver. For example,
|
||||
{"mip_display": 5} to increase the log verbosity.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
params: Optional[SolverParams] = None,
|
||||
) -> None:
|
||||
if params is None:
|
||||
params = {}
|
||||
if "randomseed" not in params.keys():
|
||||
params["randomseed"] = randint(low=0, high=1000).rvs()
|
||||
if "mip_display" not in params.keys():
|
||||
params["mip_display"] = 4
|
||||
super().__init__(
|
||||
solver_factory=pe.SolverFactory("cplex_persistent"),
|
||||
params=params,
|
||||
)
|
||||
|
||||
def _get_warm_start_regexp(self):
|
||||
return "MIP start .* with objective ([0-9.e+-]*)\\."
|
||||
|
||||
def _get_node_count_regexp(self):
|
||||
return "^[ *] *([0-9]+)"</code></pre>
|
||||
</details>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
<h2 class="section-title" id="header-classes">Classes</h2>
|
||||
<dl>
|
||||
<dt id="miplearn.solvers.pyomo.cplex.CplexPyomoSolver"><code class="flex name class">
|
||||
<span>class <span class="ident">CplexPyomoSolver</span></span>
|
||||
<span>(</span><span>params=None)</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<section class="desc"><p>An InternalSolver that uses CPLEX and the Pyomo modeling language.</p>
|
||||
<h2 id="parameters">Parameters</h2>
|
||||
<dl>
|
||||
<dt><strong><code>params</code></strong> : <code>dict</code></dt>
|
||||
<dd>Dictionary of options to pass to the Pyomo solver. For example,
|
||||
{"mip_display": 5} to increase the log verbosity.</dd>
|
||||
</dl></section>
|
||||
<details class="source">
|
||||
<summary>
|
||||
<span>Expand source code</span>
|
||||
</summary>
|
||||
<pre><code class="python">class CplexPyomoSolver(BasePyomoSolver):
|
||||
"""
|
||||
An InternalSolver that uses CPLEX and the Pyomo modeling language.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
params: dict
|
||||
Dictionary of options to pass to the Pyomo solver. For example,
|
||||
{"mip_display": 5} to increase the log verbosity.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
params: Optional[SolverParams] = None,
|
||||
) -> None:
|
||||
if params is None:
|
||||
params = {}
|
||||
if "randomseed" not in params.keys():
|
||||
params["randomseed"] = randint(low=0, high=1000).rvs()
|
||||
if "mip_display" not in params.keys():
|
||||
params["mip_display"] = 4
|
||||
super().__init__(
|
||||
solver_factory=pe.SolverFactory("cplex_persistent"),
|
||||
params=params,
|
||||
)
|
||||
|
||||
def _get_warm_start_regexp(self):
|
||||
return "MIP start .* with objective ([0-9.e+-]*)\\."
|
||||
|
||||
def _get_node_count_regexp(self):
|
||||
return "^[ *] *([0-9]+)"</code></pre>
|
||||
</details>
|
||||
<h3>Ancestors</h3>
|
||||
<ul class="hlist">
|
||||
<li><a title="miplearn.solvers.pyomo.base.BasePyomoSolver" href="base.html#miplearn.solvers.pyomo.base.BasePyomoSolver">BasePyomoSolver</a></li>
|
||||
<li><a title="miplearn.solvers.internal.InternalSolver" href="../internal.html#miplearn.solvers.internal.InternalSolver">InternalSolver</a></li>
|
||||
<li>abc.ABC</li>
|
||||
</ul>
|
||||
<h3>Inherited members</h3>
|
||||
<ul class="hlist">
|
||||
<li><code><b><a title="miplearn.solvers.pyomo.base.BasePyomoSolver" href="base.html#miplearn.solvers.pyomo.base.BasePyomoSolver">BasePyomoSolver</a></b></code>:
|
||||
<ul class="hlist">
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.add_constraint" href="../internal.html#miplearn.solvers.internal.InternalSolver.add_constraint">add_constraint</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.extract_constraint" href="../internal.html#miplearn.solvers.internal.InternalSolver.extract_constraint">extract_constraint</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.fix" href="../internal.html#miplearn.solvers.internal.InternalSolver.fix">fix</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_constraint_ids" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_constraint_ids">get_constraint_ids</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_constraint_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_constraint_sense">get_constraint_sense</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_dual" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_dual">get_dual</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_empty_solution" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_empty_solution">get_empty_solution</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_inequality_slacks" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_inequality_slacks">get_inequality_slacks</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_sense">get_sense</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_solution" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_solution">get_solution</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_value" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_value">get_value</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.is_constraint_satisfied" href="../internal.html#miplearn.solvers.internal.InternalSolver.is_constraint_satisfied">is_constraint_satisfied</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.is_infeasible" href="../internal.html#miplearn.solvers.internal.InternalSolver.is_infeasible">is_infeasible</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.relax" href="../internal.html#miplearn.solvers.internal.InternalSolver.relax">relax</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_branching_priorities" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_branching_priorities">set_branching_priorities</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_constraint_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_constraint_sense">set_constraint_sense</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_instance" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_instance">set_instance</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_warm_start" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_warm_start">set_warm_start</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.solve" href="../internal.html#miplearn.solvers.internal.InternalSolver.solve">solve</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.solve_lp" href="../internal.html#miplearn.solvers.internal.InternalSolver.solve_lp">solve_lp</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</dd>
|
||||
</dl>
|
||||
</section>
|
||||
</article>
|
||||
<nav id="sidebar">
|
||||
<h1>Index</h1>
|
||||
<div class="toc">
|
||||
<ul></ul>
|
||||
</div>
|
||||
<ul id="index">
|
||||
<li><h3>Super-module</h3>
|
||||
<ul>
|
||||
<li><code><a title="miplearn.solvers.pyomo" href="index.html">miplearn.solvers.pyomo</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><h3><a href="#header-classes">Classes</a></h3>
|
||||
<ul>
|
||||
<li>
|
||||
<h4><code><a title="miplearn.solvers.pyomo.cplex.CplexPyomoSolver" href="#miplearn.solvers.pyomo.cplex.CplexPyomoSolver">CplexPyomoSolver</a></code></h4>
|
||||
</li>
|
||||
</ul>
|
||||
</li>
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0.2/api/miplearn/solvers/pyomo/gurobi.html
Normal file
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0.2/api/miplearn/solvers/pyomo/gurobi.html
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|
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<style media="screen and (min-width: 700px)">@media screen and (min-width:700px){#sidebar{width:30%}#content{width:70%;max-width:100ch;padding:3em 4em;border-left:1px solid #ddd}pre code{font-size:1em}.item .name{font-size:1em}main{display:flex;flex-direction:row-reverse;justify-content:flex-end}.toc ul ul,#index ul{padding-left:1.5em}.toc > ul > li{margin-top:.5em}}</style>
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<style media="print">@media print{#sidebar h1{page-break-before:always}.source{display:none}}@media print{*{background:transparent !important;color:#000 !important;box-shadow:none !important;text-shadow:none !important}a[href]:after{content:" (" attr(href) ")";font-size:90%}a[href][title]:after{content:none}abbr[title]:after{content:" (" attr(title) ")"}.ir a:after,a[href^="javascript:"]:after,a[href^="#"]:after{content:""}pre,blockquote{border:1px solid #999;page-break-inside:avoid}thead{display:table-header-group}tr,img{page-break-inside:avoid}img{max-width:100% !important}@page{margin:0.5cm}p,h2,h3{orphans:3;widows:3}h1,h2,h3,h4,h5,h6{page-break-after:avoid}}</style>
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</head>
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||||
<body>
|
||||
<main>
|
||||
<article id="content">
|
||||
<header>
|
||||
<h1 class="title">Module <code>miplearn.solvers.pyomo.gurobi</code></h1>
|
||||
</header>
|
||||
<section id="section-intro">
|
||||
<details class="source">
|
||||
<summary>
|
||||
<span>Expand source code</span>
|
||||
</summary>
|
||||
<pre><code class="python"># 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.
|
||||
|
||||
import logging
|
||||
from typing import Optional
|
||||
|
||||
from pyomo import environ as pe
|
||||
from scipy.stats import randint
|
||||
|
||||
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: SolverParams = None,
|
||||
) -> None:
|
||||
if params is None:
|
||||
params = {}
|
||||
if "seed" not in params.keys():
|
||||
params["seed"] = randint(low=0, high=1000).rvs()
|
||||
super().__init__(
|
||||
solver_factory=pe.SolverFactory("gurobi_persistent"),
|
||||
params=params,
|
||||
)
|
||||
|
||||
def _extract_node_count(self, log: str) -> int:
|
||||
return max(1, int(self._pyomo_solver._solver_model.getAttr("NodeCount")))
|
||||
|
||||
def _get_warm_start_regexp(self) -> str:
|
||||
return "MIP start with objective ([0-9.e+-]*)"
|
||||
|
||||
def _get_node_count_regexp(self) -> Optional[str]:
|
||||
return None
|
||||
|
||||
def set_branching_priorities(self, priorities: BranchPriorities) -> None:
|
||||
from gurobipy import GRB
|
||||
|
||||
for varname in priorities.keys():
|
||||
var = self._varname_to_var[varname]
|
||||
for (index, priority) in priorities[varname].items():
|
||||
if priority is None:
|
||||
continue
|
||||
gvar = self._pyomo_solver._pyomo_var_to_solver_var_map[var[index]]
|
||||
gvar.setAttr(GRB.Attr.BranchPriority, int(round(priority)))</code></pre>
|
||||
</details>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
<h2 class="section-title" id="header-classes">Classes</h2>
|
||||
<dl>
|
||||
<dt id="miplearn.solvers.pyomo.gurobi.GurobiPyomoSolver"><code class="flex name class">
|
||||
<span>class <span class="ident">GurobiPyomoSolver</span></span>
|
||||
<span>(</span><span>params=None)</span>
|
||||
</code></dt>
|
||||
<dd>
|
||||
<section class="desc"><p>An InternalSolver that uses Gurobi and the Pyomo modeling language.</p>
|
||||
<h2 id="parameters">Parameters</h2>
|
||||
<dl>
|
||||
<dt><strong><code>params</code></strong> : <code>dict</code></dt>
|
||||
<dd>Dictionary of options to pass to the Pyomo solver. For example,
|
||||
{"Threads": 4} to set the number of threads.</dd>
|
||||
</dl></section>
|
||||
<details class="source">
|
||||
<summary>
|
||||
<span>Expand source code</span>
|
||||
</summary>
|
||||
<pre><code class="python">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: SolverParams = None,
|
||||
) -> None:
|
||||
if params is None:
|
||||
params = {}
|
||||
if "seed" not in params.keys():
|
||||
params["seed"] = randint(low=0, high=1000).rvs()
|
||||
super().__init__(
|
||||
solver_factory=pe.SolverFactory("gurobi_persistent"),
|
||||
params=params,
|
||||
)
|
||||
|
||||
def _extract_node_count(self, log: str) -> int:
|
||||
return max(1, int(self._pyomo_solver._solver_model.getAttr("NodeCount")))
|
||||
|
||||
def _get_warm_start_regexp(self) -> str:
|
||||
return "MIP start with objective ([0-9.e+-]*)"
|
||||
|
||||
def _get_node_count_regexp(self) -> Optional[str]:
|
||||
return None
|
||||
|
||||
def set_branching_priorities(self, priorities: BranchPriorities) -> None:
|
||||
from gurobipy import GRB
|
||||
|
||||
for varname in priorities.keys():
|
||||
var = self._varname_to_var[varname]
|
||||
for (index, priority) in priorities[varname].items():
|
||||
if priority is None:
|
||||
continue
|
||||
gvar = self._pyomo_solver._pyomo_var_to_solver_var_map[var[index]]
|
||||
gvar.setAttr(GRB.Attr.BranchPriority, int(round(priority)))</code></pre>
|
||||
</details>
|
||||
<h3>Ancestors</h3>
|
||||
<ul class="hlist">
|
||||
<li><a title="miplearn.solvers.pyomo.base.BasePyomoSolver" href="base.html#miplearn.solvers.pyomo.base.BasePyomoSolver">BasePyomoSolver</a></li>
|
||||
<li><a title="miplearn.solvers.internal.InternalSolver" href="../internal.html#miplearn.solvers.internal.InternalSolver">InternalSolver</a></li>
|
||||
<li>abc.ABC</li>
|
||||
</ul>
|
||||
<h3>Inherited members</h3>
|
||||
<ul class="hlist">
|
||||
<li><code><b><a title="miplearn.solvers.pyomo.base.BasePyomoSolver" href="base.html#miplearn.solvers.pyomo.base.BasePyomoSolver">BasePyomoSolver</a></b></code>:
|
||||
<ul class="hlist">
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.add_constraint" href="../internal.html#miplearn.solvers.internal.InternalSolver.add_constraint">add_constraint</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.extract_constraint" href="../internal.html#miplearn.solvers.internal.InternalSolver.extract_constraint">extract_constraint</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.fix" href="../internal.html#miplearn.solvers.internal.InternalSolver.fix">fix</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_constraint_ids" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_constraint_ids">get_constraint_ids</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_constraint_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_constraint_sense">get_constraint_sense</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_dual" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_dual">get_dual</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_empty_solution" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_empty_solution">get_empty_solution</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_inequality_slacks" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_inequality_slacks">get_inequality_slacks</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_sense">get_sense</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_solution" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_solution">get_solution</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_value" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_value">get_value</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.is_constraint_satisfied" href="../internal.html#miplearn.solvers.internal.InternalSolver.is_constraint_satisfied">is_constraint_satisfied</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.is_infeasible" href="../internal.html#miplearn.solvers.internal.InternalSolver.is_infeasible">is_infeasible</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.relax" href="../internal.html#miplearn.solvers.internal.InternalSolver.relax">relax</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_branching_priorities" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_branching_priorities">set_branching_priorities</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_constraint_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_constraint_sense">set_constraint_sense</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_instance" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_instance">set_instance</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_warm_start" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_warm_start">set_warm_start</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.solve" href="../internal.html#miplearn.solvers.internal.InternalSolver.solve">solve</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.solve_lp" href="../internal.html#miplearn.solvers.internal.InternalSolver.solve_lp">solve_lp</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</dd>
|
||||
</dl>
|
||||
</section>
|
||||
</article>
|
||||
<nav id="sidebar">
|
||||
<h1>Index</h1>
|
||||
<div class="toc">
|
||||
<ul></ul>
|
||||
</div>
|
||||
<ul id="index">
|
||||
<li><h3>Super-module</h3>
|
||||
<ul>
|
||||
<li><code><a title="miplearn.solvers.pyomo" href="index.html">miplearn.solvers.pyomo</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><h3><a href="#header-classes">Classes</a></h3>
|
||||
<ul>
|
||||
<li>
|
||||
<h4><code><a title="miplearn.solvers.pyomo.gurobi.GurobiPyomoSolver" href="#miplearn.solvers.pyomo.gurobi.GurobiPyomoSolver">GurobiPyomoSolver</a></code></h4>
|
||||
</li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
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<p>Generated by <a href="https://pdoc3.github.io/pdoc"><cite>pdoc</cite> 0.7.0</a>.</p>
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<script>hljs.initHighlightingOnLoad()</script>
|
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</body>
|
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</html>
|
||||
88
0.2/api/miplearn/solvers/pyomo/index.html
Normal file
88
0.2/api/miplearn/solvers/pyomo/index.html
Normal file
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<!doctype html>
|
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<html lang="en">
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<head>
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<title>miplearn.solvers.pyomo API documentation</title>
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|
||||
<body>
|
||||
<main>
|
||||
<article id="content">
|
||||
<header>
|
||||
<h1 class="title">Module <code>miplearn.solvers.pyomo</code></h1>
|
||||
</header>
|
||||
<section id="section-intro">
|
||||
<details class="source">
|
||||
<summary>
|
||||
<span>Expand source code</span>
|
||||
</summary>
|
||||
<pre><code class="python"># 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.</code></pre>
|
||||
</details>
|
||||
</section>
|
||||
<section>
|
||||
<h2 class="section-title" id="header-submodules">Sub-modules</h2>
|
||||
<dl>
|
||||
<dt><code class="name"><a title="miplearn.solvers.pyomo.base" href="base.html">miplearn.solvers.pyomo.base</a></code></dt>
|
||||
<dd>
|
||||
<section class="desc"></section>
|
||||
</dd>
|
||||
<dt><code class="name"><a title="miplearn.solvers.pyomo.cplex" href="cplex.html">miplearn.solvers.pyomo.cplex</a></code></dt>
|
||||
<dd>
|
||||
<section class="desc"></section>
|
||||
</dd>
|
||||
<dt><code class="name"><a title="miplearn.solvers.pyomo.gurobi" href="gurobi.html">miplearn.solvers.pyomo.gurobi</a></code></dt>
|
||||
<dd>
|
||||
<section class="desc"></section>
|
||||
</dd>
|
||||
<dt><code class="name"><a title="miplearn.solvers.pyomo.xpress" href="xpress.html">miplearn.solvers.pyomo.xpress</a></code></dt>
|
||||
<dd>
|
||||
<section class="desc"></section>
|
||||
</dd>
|
||||
</dl>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
<section>
|
||||
</section>
|
||||
</article>
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||||
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<h1>Index</h1>
|
||||
<div class="toc">
|
||||
<ul></ul>
|
||||
</div>
|
||||
<ul id="index">
|
||||
<li><h3>Super-module</h3>
|
||||
<ul>
|
||||
<li><code><a title="miplearn.solvers" href="../index.html">miplearn.solvers</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><h3><a href="#header-submodules">Sub-modules</a></h3>
|
||||
<ul>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base" href="base.html">miplearn.solvers.pyomo.base</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.cplex" href="cplex.html">miplearn.solvers.pyomo.cplex</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.gurobi" href="gurobi.html">miplearn.solvers.pyomo.gurobi</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.xpress" href="xpress.html">miplearn.solvers.pyomo.xpress</a></code></li>
|
||||
</ul>
|
||||
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174
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174
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<main>
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<article id="content">
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<header>
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<h1 class="title">Module <code>miplearn.solvers.pyomo.xpress</code></h1>
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</header>
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<section id="section-intro">
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<details class="source">
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<summary>
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<span>Expand source code</span>
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</summary>
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<pre><code class="python"># 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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import logging
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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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logger = logging.getLogger(__name__)
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class XpressPyomoSolver(BasePyomoSolver):
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"""
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An InternalSolver that uses XPRESS and the Pyomo modeling language.
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||||
Parameters
|
||||
----------
|
||||
params: dict
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||||
Dictionary of options to pass to the Pyomo solver. For example,
|
||||
{"Threads": 4} to set the number of threads.
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"""
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def __init__(self, params: SolverParams = None) -> 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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super().__init__(
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solver_factory=pe.SolverFactory("xpress_persistent"),
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params=params,
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)</code></pre>
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</details>
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</section>
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<section>
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</section>
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<section>
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</section>
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<section>
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</section>
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<section>
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<h2 class="section-title" id="header-classes">Classes</h2>
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<dl>
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<dt id="miplearn.solvers.pyomo.xpress.XpressPyomoSolver"><code class="flex name class">
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<span>class <span class="ident">XpressPyomoSolver</span></span>
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<span>(</span><span>params=None)</span>
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</code></dt>
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<dd>
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<section class="desc"><p>An InternalSolver that uses XPRESS and the Pyomo modeling language.</p>
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<h2 id="parameters">Parameters</h2>
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<dl>
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||||
<dt><strong><code>params</code></strong> : <code>dict</code></dt>
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||||
<dd>Dictionary of options to pass to the Pyomo solver. For example,
|
||||
{"Threads": 4} to set the number of threads.</dd>
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</dl></section>
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<details class="source">
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||||
<summary>
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<span>Expand source code</span>
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||||
</summary>
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||||
<pre><code class="python">class XpressPyomoSolver(BasePyomoSolver):
|
||||
"""
|
||||
An InternalSolver that uses XPRESS 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: SolverParams = None) -> None:
|
||||
if params is None:
|
||||
params = {}
|
||||
if "randomseed" not in params.keys():
|
||||
params["randomseed"] = randint(low=0, high=1000).rvs()
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||||
super().__init__(
|
||||
solver_factory=pe.SolverFactory("xpress_persistent"),
|
||||
params=params,
|
||||
)</code></pre>
|
||||
</details>
|
||||
<h3>Ancestors</h3>
|
||||
<ul class="hlist">
|
||||
<li><a title="miplearn.solvers.pyomo.base.BasePyomoSolver" href="base.html#miplearn.solvers.pyomo.base.BasePyomoSolver">BasePyomoSolver</a></li>
|
||||
<li><a title="miplearn.solvers.internal.InternalSolver" href="../internal.html#miplearn.solvers.internal.InternalSolver">InternalSolver</a></li>
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||||
<li>abc.ABC</li>
|
||||
</ul>
|
||||
<h3>Inherited members</h3>
|
||||
<ul class="hlist">
|
||||
<li><code><b><a title="miplearn.solvers.pyomo.base.BasePyomoSolver" href="base.html#miplearn.solvers.pyomo.base.BasePyomoSolver">BasePyomoSolver</a></b></code>:
|
||||
<ul class="hlist">
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.add_constraint" href="../internal.html#miplearn.solvers.internal.InternalSolver.add_constraint">add_constraint</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.extract_constraint" href="../internal.html#miplearn.solvers.internal.InternalSolver.extract_constraint">extract_constraint</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.fix" href="../internal.html#miplearn.solvers.internal.InternalSolver.fix">fix</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_constraint_ids" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_constraint_ids">get_constraint_ids</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_constraint_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_constraint_sense">get_constraint_sense</a></code></li>
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||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_dual" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_dual">get_dual</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_empty_solution" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_empty_solution">get_empty_solution</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_inequality_slacks" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_inequality_slacks">get_inequality_slacks</a></code></li>
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||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_sense">get_sense</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_solution" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_solution">get_solution</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.get_value" href="../internal.html#miplearn.solvers.internal.InternalSolver.get_value">get_value</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.is_constraint_satisfied" href="../internal.html#miplearn.solvers.internal.InternalSolver.is_constraint_satisfied">is_constraint_satisfied</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.is_infeasible" href="../internal.html#miplearn.solvers.internal.InternalSolver.is_infeasible">is_infeasible</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.relax" href="../internal.html#miplearn.solvers.internal.InternalSolver.relax">relax</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_branching_priorities" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_branching_priorities">set_branching_priorities</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_constraint_sense" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_constraint_sense">set_constraint_sense</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_instance" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_instance">set_instance</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.set_warm_start" href="../internal.html#miplearn.solvers.internal.InternalSolver.set_warm_start">set_warm_start</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.solve" href="../internal.html#miplearn.solvers.internal.InternalSolver.solve">solve</a></code></li>
|
||||
<li><code><a title="miplearn.solvers.pyomo.base.BasePyomoSolver.solve_lp" href="../internal.html#miplearn.solvers.internal.InternalSolver.solve_lp">solve_lp</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</dd>
|
||||
</dl>
|
||||
</section>
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||||
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<h1>Index</h1>
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<div class="toc">
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<ul></ul>
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</div>
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<ul id="index">
|
||||
<li><h3>Super-module</h3>
|
||||
<ul>
|
||||
<li><code><a title="miplearn.solvers.pyomo" href="index.html">miplearn.solvers.pyomo</a></code></li>
|
||||
</ul>
|
||||
</li>
|
||||
<li><h3><a href="#header-classes">Classes</a></h3>
|
||||
<ul>
|
||||
<li>
|
||||
<h4><code><a title="miplearn.solvers.pyomo.xpress.XpressPyomoSolver" href="#miplearn.solvers.pyomo.xpress.XpressPyomoSolver">XpressPyomoSolver</a></code></h4>
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