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https://github.com/ANL-CEEESA/MIPLearn.git
synced 2025-12-07 18:08:51 -06:00
Sort methods
This commit is contained in:
@@ -81,6 +81,191 @@ class GurobiSolver(InternalSolver):
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self.gp.GRB.Callback.MIPNODE,
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]
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@overrides
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def add_constraint(self, constr: Constraint, name: str) -> None:
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assert self.model is not None
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lhs = self.gp.quicksum(
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self._varname_to_var[varname] * coeff
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for (varname, coeff) in constr.lhs.items()
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)
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if constr.sense == "=":
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self.model.addConstr(lhs == constr.rhs, name=name)
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elif constr.sense == "<":
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self.model.addConstr(lhs <= constr.rhs, name=name)
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else:
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self.model.addConstr(lhs >= constr.rhs, name=name)
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self._dirty = True
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self._has_lp_solution = False
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self._has_mip_solution = False
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@overrides
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def are_callbacks_supported(self) -> bool:
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return True
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@overrides
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def build_test_instance_infeasible(self) -> Instance:
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return GurobiTestInstanceInfeasible()
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@overrides
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def build_test_instance_knapsack(self) -> Instance:
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return GurobiTestInstanceKnapsack(
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weights=[23.0, 26.0, 20.0, 18.0],
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prices=[505.0, 352.0, 458.0, 220.0],
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capacity=67.0,
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)
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@overrides
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def build_test_instance_redundancy(self) -> Instance:
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return GurobiTestInstanceRedundancy()
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@overrides
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def clone(self) -> "GurobiSolver":
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return GurobiSolver(
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params=self.params,
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lazy_cb_frequency=self.lazy_cb_frequency,
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)
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@overrides
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def fix(self, solution: Solution) -> None:
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self._raise_if_callback()
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for (varname, value) in solution.items():
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if value is None:
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continue
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var = self._varname_to_var[varname]
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var.vtype = self.gp.GRB.CONTINUOUS
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var.lb = value
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var.ub = value
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@overrides
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def get_dual(self, cid: str) -> float:
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assert self.model is not None
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c = self.model.getConstrByName(cid)
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if self.is_infeasible():
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return c.farkasDual
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else:
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return c.pi
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@overrides
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def get_constraint_attrs(self) -> List[str]:
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return [
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"basis_status",
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"category",
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"dual_value",
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"lazy",
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"lhs",
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"rhs",
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"sa_rhs_down",
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"sa_rhs_up",
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"sense",
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"slack",
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"user_features",
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]
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@overrides
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def get_constraints(self) -> Dict[str, Constraint]:
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assert self.model is not None
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self._raise_if_callback()
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if self._dirty:
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self.model.update()
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self._dirty = False
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constraints: Dict[str, Constraint] = {}
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for c in self.model.getConstrs():
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constr = self._parse_gurobi_constraint(c)
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assert c.constrName not in constraints
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constraints[c.constrName] = constr
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return constraints
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@overrides
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def get_sense(self) -> str:
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assert self.model is not None
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if self.model.modelSense == 1:
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return "min"
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else:
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return "max"
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@overrides
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def get_solution(self) -> Optional[Solution]:
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assert self.model is not None
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if self.cb_where is not None:
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if self.cb_where == self.gp.GRB.Callback.MIPNODE:
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return {
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v.varName: self.model.cbGetNodeRel(v) for v in self.model.getVars()
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}
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elif self.cb_where == self.gp.GRB.Callback.MIPSOL:
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return {
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v.varName: self.model.cbGetSolution(v) for v in self.model.getVars()
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}
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else:
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raise Exception(
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f"get_solution can only be called from a callback "
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f"when cb_where is either MIPNODE or MIPSOL"
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)
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if self.model.solCount == 0:
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return None
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return {v.varName: v.x for v in self.model.getVars()}
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@overrides
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def get_variable_attrs(self) -> List[str]:
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return [
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"basis_status",
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"category",
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"lower_bound",
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"obj_coeff",
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"reduced_cost",
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"sa_lb_down",
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"sa_lb_up",
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"sa_obj_down",
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"sa_obj_up",
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"sa_ub_down",
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"sa_ub_up",
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"type",
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"upper_bound",
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"user_features",
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"value",
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]
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@overrides
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def get_variable_names(self) -> List[VariableName]:
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self._raise_if_callback()
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assert self.model is not None
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return [v.varName for v in self.model.getVars()]
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@overrides
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def get_variables(self) -> Dict[str, Variable]:
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assert self.model is not None
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variables = {}
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for gp_var in self.model.getVars():
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name = gp_var.varName
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assert len(name) > 0, f"empty variable name detected"
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assert name not in variables, f"duplicated variable name detected: {name}"
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var = self._parse_gurobi_var(gp_var)
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variables[name] = var
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return variables
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@overrides
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def is_constraint_satisfied(self, constr: Constraint, tol: float = 1e-6) -> bool:
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lhs = 0.0
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for (varname, coeff) in constr.lhs.items():
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var = self._varname_to_var[varname]
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lhs += self._get_value(var) * coeff
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if constr.sense == "<":
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return lhs <= constr.rhs + tol
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elif constr.sense == ">":
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return lhs >= constr.rhs - tol
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else:
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return abs(constr.rhs - lhs) < abs(tol)
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@overrides
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def is_infeasible(self) -> bool:
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assert self.model is not None
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return self.model.status in [self.gp.GRB.INFEASIBLE, self.gp.GRB.INF_OR_UNBD]
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@overrides
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def remove_constraint(self, name: str) -> None:
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assert self.model is not None
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constr = self.model.getConstrByName(name)
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self.model.remove(constr)
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@overrides
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def set_instance(
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self,
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@@ -96,66 +281,14 @@ class GurobiSolver(InternalSolver):
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self.model.update()
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self._update_vars()
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def _raise_if_callback(self) -> None:
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if self.cb_where is not None:
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raise Exception("method cannot be called from a callback")
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def _update_vars(self) -> None:
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assert self.model is not None
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self._varname_to_var.clear()
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self._original_vtype = {}
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self._bin_vars.clear()
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for var in self.model.getVars():
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assert var.varName not in self._varname_to_var, (
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f"Duplicated variable name detected: {var.varName}. "
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f"Unique variable names are currently required."
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)
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self._varname_to_var[var.varName] = var
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assert var.vtype in ["B", "C"], (
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"Only binary and continuous variables are currently supported. "
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"Variable {var.varName} has type {var.vtype}."
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)
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self._original_vtype[var] = var.vtype
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if var.vtype == "B":
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self._bin_vars.append(var)
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def _apply_params(self, streams: List[Any]) -> None:
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assert self.model is not None
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with _RedirectOutput(streams):
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for (name, value) in self.params.items():
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self.model.setParam(name, value)
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@overrides
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def solve_lp(
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self,
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tee: bool = False,
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) -> LPSolveStats:
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def set_warm_start(self, solution: Solution) -> None:
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self._raise_if_callback()
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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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self._apply_params(streams)
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assert self.model is not None
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for var in self._bin_vars:
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var.vtype = self.gp.GRB.CONTINUOUS
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var.lb = 0.0
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var.ub = 1.0
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with _RedirectOutput(streams):
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self.model.optimize()
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self._dirty = False
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for var in self._bin_vars:
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var.vtype = self.gp.GRB.BINARY
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log = streams[0].getvalue()
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self._has_lp_solution = self.model.solCount > 0
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self._has_mip_solution = False
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opt_value = None
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if not self.is_infeasible():
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opt_value = self.model.objVal
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return LPSolveStats(
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lp_value=opt_value,
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lp_log=log,
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lp_wallclock_time=self.model.runtime,
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)
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self._clear_warm_start()
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for (var_name, value) in solution.items():
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var = self._varname_to_var[var_name]
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if value is not None:
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var.start = value
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@overrides
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def solve(
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@@ -235,62 +368,73 @@ class GurobiSolver(InternalSolver):
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)
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@overrides
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def get_solution(self) -> Optional[Solution]:
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def solve_lp(
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self,
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tee: bool = False,
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) -> LPSolveStats:
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self._raise_if_callback()
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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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self._apply_params(streams)
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assert self.model is not None
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if self.cb_where is not None:
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if self.cb_where == self.gp.GRB.Callback.MIPNODE:
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return {
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v.varName: self.model.cbGetNodeRel(v) for v in self.model.getVars()
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}
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elif self.cb_where == self.gp.GRB.Callback.MIPSOL:
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return {
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v.varName: self.model.cbGetSolution(v) for v in self.model.getVars()
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}
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else:
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raise Exception(
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f"get_solution can only be called from a callback "
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f"when cb_where is either MIPNODE or MIPSOL"
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)
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if self.model.solCount == 0:
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for var in self._bin_vars:
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var.vtype = self.gp.GRB.CONTINUOUS
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var.lb = 0.0
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var.ub = 1.0
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with _RedirectOutput(streams):
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self.model.optimize()
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self._dirty = False
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for var in self._bin_vars:
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var.vtype = self.gp.GRB.BINARY
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log = streams[0].getvalue()
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self._has_lp_solution = self.model.solCount > 0
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self._has_mip_solution = False
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opt_value = None
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if not self.is_infeasible():
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opt_value = self.model.objVal
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return LPSolveStats(
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lp_value=opt_value,
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lp_log=log,
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lp_wallclock_time=self.model.runtime,
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)
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@overrides
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def relax(self) -> None:
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assert self.model is not None
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self.model.update()
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self.model = self.model.relax()
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self._update_vars()
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def _apply_params(self, streams: List[Any]) -> None:
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assert self.model is not None
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with _RedirectOutput(streams):
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for (name, value) in self.params.items():
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self.model.setParam(name, value)
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def _clear_warm_start(self) -> None:
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for var in self._varname_to_var.values():
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var.start = self.gp.GRB.UNDEFINED
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@staticmethod
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def _extract(
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log: str,
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regexp: str,
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default: Optional[str] = None,
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) -> Optional[str]:
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value = default
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for line in log.splitlines():
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matches = re.findall(regexp, line)
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if len(matches) == 0:
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continue
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value = matches[0]
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return value
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def _extract_warm_start_value(self, log: str) -> Optional[float]:
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ws = self._extract(log, "MIP start with objective ([0-9.e+-]*)")
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if ws is None:
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return None
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return {v.varName: v.x for v in self.model.getVars()}
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@overrides
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def get_variable_names(self) -> List[VariableName]:
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self._raise_if_callback()
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assert self.model is not None
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return [v.varName for v in self.model.getVars()]
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@overrides
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def set_warm_start(self, solution: Solution) -> None:
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self._raise_if_callback()
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self._clear_warm_start()
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for (var_name, value) in solution.items():
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var = self._varname_to_var[var_name]
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if value is not None:
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var.start = value
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@overrides
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def get_sense(self) -> str:
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assert self.model is not None
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if self.model.modelSense == 1:
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return "min"
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else:
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return "max"
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@overrides
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def is_infeasible(self) -> bool:
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assert self.model is not None
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return self.model.status in [self.gp.GRB.INFEASIBLE, self.gp.GRB.INF_OR_UNBD]
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@overrides
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def get_dual(self, cid: str) -> float:
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assert self.model is not None
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c = self.model.getConstrByName(cid)
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if self.is_infeasible():
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return c.farkasDual
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else:
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return c.pi
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return float(ws)
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def _get_value(self, var: Any) -> float:
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assert self.model is not None
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@@ -305,132 +449,6 @@ class GurobiSolver(InternalSolver):
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"get_value cannot be called from cb_where=%s" % self.cb_where
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)
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@overrides
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def add_constraint(self, constr: Constraint, name: str) -> None:
|
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assert self.model is not None
|
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lhs = self.gp.quicksum(
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self._varname_to_var[varname] * coeff
|
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for (varname, coeff) in constr.lhs.items()
|
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)
|
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if constr.sense == "=":
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self.model.addConstr(lhs == constr.rhs, name=name)
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elif constr.sense == "<":
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self.model.addConstr(lhs <= constr.rhs, name=name)
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else:
|
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self.model.addConstr(lhs >= constr.rhs, name=name)
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self._dirty = True
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self._has_lp_solution = False
|
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self._has_mip_solution = False
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|
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@overrides
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def remove_constraint(self, name: str) -> None:
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assert self.model is not None
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constr = self.model.getConstrByName(name)
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self.model.remove(constr)
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@overrides
|
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def is_constraint_satisfied(self, constr: Constraint, tol: float = 1e-6) -> bool:
|
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lhs = 0.0
|
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for (varname, coeff) in constr.lhs.items():
|
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var = self._varname_to_var[varname]
|
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lhs += self._get_value(var) * coeff
|
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if constr.sense == "<":
|
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return lhs <= constr.rhs + tol
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elif constr.sense == ">":
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return lhs >= constr.rhs - tol
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else:
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return abs(constr.rhs - lhs) < abs(tol)
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def _clear_warm_start(self) -> None:
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for var in self._varname_to_var.values():
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var.start = self.gp.GRB.UNDEFINED
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|
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@overrides
|
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def fix(self, solution: Solution) -> None:
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self._raise_if_callback()
|
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for (varname, value) in solution.items():
|
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if value is None:
|
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continue
|
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var = self._varname_to_var[varname]
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var.vtype = self.gp.GRB.CONTINUOUS
|
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var.lb = value
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var.ub = value
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||||
|
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@overrides
|
||||
def relax(self) -> None:
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assert self.model is not None
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self.model.update()
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self.model = self.model.relax()
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self._update_vars()
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|
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def _extract_warm_start_value(self, log: str) -> Optional[float]:
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ws = self.__extract(log, "MIP start with objective ([0-9.e+-]*)")
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if ws is None:
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return None
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return float(ws)
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|
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@staticmethod
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def __extract(
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log: str,
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regexp: str,
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||||
default: Optional[str] = None,
|
||||
) -> Optional[str]:
|
||||
value = default
|
||||
for line in log.splitlines():
|
||||
matches = re.findall(regexp, line)
|
||||
if len(matches) == 0:
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||||
continue
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value = matches[0]
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return value
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|
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def __getstate__(self) -> Dict:
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return {
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"params": self.params,
|
||||
"lazy_cb_where": self.lazy_cb_where,
|
||||
}
|
||||
|
||||
def __setstate__(self, state: Dict) -> None:
|
||||
self.params = state["params"]
|
||||
self.lazy_cb_where = state["lazy_cb_where"]
|
||||
self.instance = None
|
||||
self.model = None
|
||||
self.cb_where = None
|
||||
|
||||
@overrides
|
||||
def clone(self) -> "GurobiSolver":
|
||||
return GurobiSolver(
|
||||
params=self.params,
|
||||
lazy_cb_frequency=self.lazy_cb_frequency,
|
||||
)
|
||||
|
||||
@overrides
|
||||
def build_test_instance_infeasible(self) -> Instance:
|
||||
return GurobiTestInstanceInfeasible()
|
||||
|
||||
@overrides
|
||||
def build_test_instance_redundancy(self) -> Instance:
|
||||
return GurobiTestInstanceRedundancy()
|
||||
|
||||
@overrides
|
||||
def build_test_instance_knapsack(self) -> Instance:
|
||||
return GurobiTestInstanceKnapsack(
|
||||
weights=[23.0, 26.0, 20.0, 18.0],
|
||||
prices=[505.0, 352.0, 458.0, 220.0],
|
||||
capacity=67.0,
|
||||
)
|
||||
|
||||
@overrides
|
||||
def get_variables(self) -> Dict[str, Variable]:
|
||||
assert self.model is not None
|
||||
variables = {}
|
||||
for gp_var in self.model.getVars():
|
||||
name = gp_var.varName
|
||||
assert len(name) > 0, f"empty variable name detected"
|
||||
assert name not in variables, f"duplicated variable name detected: {name}"
|
||||
var = self._parse_gurobi_var(gp_var)
|
||||
variables[name] = var
|
||||
return variables
|
||||
|
||||
def _parse_gurobi_var(self, gp_var: Any) -> Variable:
|
||||
assert self.model is not None
|
||||
var = Variable()
|
||||
@@ -462,20 +480,6 @@ class GurobiSolver(InternalSolver):
|
||||
var.value = gp_var.x
|
||||
return var
|
||||
|
||||
@overrides
|
||||
def get_constraints(self) -> Dict[str, Constraint]:
|
||||
assert self.model is not None
|
||||
self._raise_if_callback()
|
||||
if self._dirty:
|
||||
self.model.update()
|
||||
self._dirty = False
|
||||
constraints: Dict[str, Constraint] = {}
|
||||
for c in self.model.getConstrs():
|
||||
constr = self._parse_gurobi_constraint(c)
|
||||
assert c.constrName not in constraints
|
||||
constraints[c.constrName] = constr
|
||||
return constraints
|
||||
|
||||
def _parse_gurobi_constraint(self, gp_constr: Any) -> Constraint:
|
||||
assert self.model is not None
|
||||
expr = self.model.getRow(gp_constr)
|
||||
@@ -501,45 +505,41 @@ class GurobiSolver(InternalSolver):
|
||||
constr.slack = gp_constr.slack
|
||||
return constr
|
||||
|
||||
@overrides
|
||||
def are_callbacks_supported(self) -> bool:
|
||||
return True
|
||||
def _raise_if_callback(self) -> None:
|
||||
if self.cb_where is not None:
|
||||
raise Exception("method cannot be called from a callback")
|
||||
|
||||
@overrides
|
||||
def get_constraint_attrs(self) -> List[str]:
|
||||
return [
|
||||
"basis_status",
|
||||
"category",
|
||||
"dual_value",
|
||||
"lazy",
|
||||
"lhs",
|
||||
"rhs",
|
||||
"sa_rhs_down",
|
||||
"sa_rhs_up",
|
||||
"sense",
|
||||
"slack",
|
||||
"user_features",
|
||||
]
|
||||
def _update_vars(self) -> None:
|
||||
assert self.model is not None
|
||||
self._varname_to_var.clear()
|
||||
self._original_vtype = {}
|
||||
self._bin_vars.clear()
|
||||
for var in self.model.getVars():
|
||||
assert var.varName not in self._varname_to_var, (
|
||||
f"Duplicated variable name detected: {var.varName}. "
|
||||
f"Unique variable names are currently required."
|
||||
)
|
||||
self._varname_to_var[var.varName] = var
|
||||
assert var.vtype in ["B", "C"], (
|
||||
"Only binary and continuous variables are currently supported. "
|
||||
"Variable {var.varName} has type {var.vtype}."
|
||||
)
|
||||
self._original_vtype[var] = var.vtype
|
||||
if var.vtype == "B":
|
||||
self._bin_vars.append(var)
|
||||
|
||||
@overrides
|
||||
def get_variable_attrs(self) -> List[str]:
|
||||
return [
|
||||
"basis_status",
|
||||
"category",
|
||||
"lower_bound",
|
||||
"obj_coeff",
|
||||
"reduced_cost",
|
||||
"sa_lb_down",
|
||||
"sa_lb_up",
|
||||
"sa_obj_down",
|
||||
"sa_obj_up",
|
||||
"sa_ub_down",
|
||||
"sa_ub_up",
|
||||
"type",
|
||||
"upper_bound",
|
||||
"user_features",
|
||||
"value",
|
||||
]
|
||||
def __getstate__(self) -> Dict:
|
||||
return {
|
||||
"params": self.params,
|
||||
"lazy_cb_where": self.lazy_cb_where,
|
||||
}
|
||||
|
||||
def __setstate__(self, state: Dict) -> None:
|
||||
self.params = state["params"]
|
||||
self.lazy_cb_where = state["lazy_cb_where"]
|
||||
self.instance = None
|
||||
self.model = None
|
||||
self.cb_where = None
|
||||
|
||||
|
||||
class GurobiTestInstanceInfeasible(Instance):
|
||||
|
||||
Reference in New Issue
Block a user