Implement bulk constraint methods

miplearn/solvers/gurobi.py

@@ -111,10 +111,59 @@ class GurobiSolver(InternalSolver):
         self._has_lp_solution = False
         self._has_mip_solution = False
 
+    @overrides
+    def add_constraints(self, cf: ConstraintFeatures) -> None:
+        assert cf.names is not None
+        assert cf.senses is not None
+        assert cf.lhs is not None
+        assert cf.rhs is not None
+        assert self.model is not None
+        for i in range(len(cf.names)):
+            sense = cf.senses[i]
+            lhs = self.gp.quicksum(
+                self._varname_to_var[varname] * coeff for (varname, coeff) in cf.lhs[i]
+            )
+            if sense == "=":
+                self.model.addConstr(lhs == cf.rhs[i], name=cf.names[i])
+            elif sense == "<":
+                self.model.addConstr(lhs <= cf.rhs[i], name=cf.names[i])
+            else:
+                self.model.addConstr(lhs >= cf.rhs[i], name=cf.names[i])
+        self.model.update()
+        self._dirty = True
+        self._has_lp_solution = False
+        self._has_mip_solution = False
+
     @overrides
     def are_callbacks_supported(self) -> bool:
         return True
 
+    @overrides
+    def are_constraints_satisfied(
+        self,
+        cf: ConstraintFeatures,
+        tol: float = 1e-5,
+    ) -> List[bool]:
+        assert cf.names is not None
+        assert cf.senses is not None
+        assert cf.lhs is not None
+        assert cf.rhs is not None
+        assert self.model is not None
+        result = []
+        for i in range(len(cf.names)):
+            sense = cf.senses[i]
+            lhs = sum(
+                self._varname_to_var[varname].x * coeff
+                for (varname, coeff) in cf.lhs[i]
+            )
+            if sense == "<":
+                result.append(lhs <= cf.rhs[i] + tol)
+            elif sense == ">":
+                result.append(lhs >= cf.rhs[i] - tol)
+            else:
+                result.append(abs(cf.rhs[i] - lhs) <= tol)
+        return result
+
     @overrides
     def build_test_instance_infeasible(self) -> Instance:
         return GurobiTestInstanceInfeasible()
@@ -477,6 +526,13 @@ class GurobiSolver(InternalSolver):
         constr = self.model.getConstrByName(name)
         self.model.remove(constr)
 
+    @overrides
+    def remove_constraints(self, names: List[str]) -> None:
+        assert self.model is not None
+        constrs = [self.model.getConstrByName(n) for n in names]
+        self.model.remove(constrs)
+        self.model.update()
+
     @overrides
     def set_instance(
         self,

miplearn/solvers/internal.py

@@ -186,6 +186,22 @@ class InternalSolver(ABC):
         """
         pass
 
+    @abstractmethod
+    def add_constraints(self, cf: ConstraintFeatures) -> None:
+        """Adds the given constraints to the model."""
+        pass
+
+    @abstractmethod
+    def are_constraints_satisfied(
+        self,
+        cf: ConstraintFeatures,
+        tol: float = 1e-5,
+    ) -> List[bool]:
+        """
+        Checks whether the current solution satisfies the given constraints.
+        """
+        pass
+
     @abstractmethod
     def remove_constraint(self, name: str) -> None:
         """
@@ -193,6 +209,13 @@ class InternalSolver(ABC):
         """
         pass
 
+    @abstractmethod
+    def remove_constraints(self, names: List[str]) -> None:
+        """
+        Removes the given constraints from the model.
+        """
+        pass
+
     @abstractmethod
     def is_constraint_satisfied_old(
         self, constr: Constraint, tol: float = 1e-6
@@ -235,6 +258,14 @@ class InternalSolver(ABC):
 
     @abstractmethod
     def build_test_instance_knapsack(self) -> Instance:
+        """
+        Returns an instance corresponding to the following MIP, for testing purposes:
+
+          maximize  505 x0 + 352 x1 + 458 x2 + 220 x3
+          s.t.      eq_capacity: z = 23 x0 + 26 x1 + 20 x2 + 18 x3
+                    x0, x1, x2, x3 binary
+                    0 <= z <= 67 continuous
+        """
         pass
 
     def are_callbacks_supported(self) -> bool:
@@ -250,12 +281,28 @@ class InternalSolver(ABC):
         with_static: bool = True,
         with_sa: bool = True,
     ) -> VariableFeatures:
+        """
+        Returns a description of the decision variables in the problem.
+
+        Parameters
+        ----------
+        with_static: bool
+            If True, include features that do not change during the solution process,
+            such as variable types and names. This parameter is used to reduce the
+            amount of duplicated data collected by LearningSolver. Features that do
+            not change are only collected once.
+        with_sa: bool
+            If True, collect sensitivity analysis information. For large models,
+            collecting this information may be expensive, so this parameter is useful
+            for reducing running times.
+        """
         pass
 
     @abstractmethod
     def get_constraint_attrs(self) -> List[str]:
         """
-        Returns a list of constraint attributes supported by this solver.
+        Returns a list of constraint attributes supported by this solver. Used for
+        testing purposes only.
         """
 
         pass
@@ -263,6 +310,7 @@ class InternalSolver(ABC):
     @abstractmethod
     def get_variable_attrs(self) -> List[str]:
         """
-        Returns a list of variable attributes supported by this solver.
+        Returns a list of variable attributes supported by this solver. Used for
+        testing purposes only.
         """
         pass

miplearn/solvers/pyomo/base.py

@@ -98,10 +98,60 @@ class BasePyomoSolver(InternalSolver):
         self._has_lp_solution = False
         self._has_mip_solution = False
 
+    @overrides
+    def add_constraints(self, cf: ConstraintFeatures) -> None:
+        assert cf.names is not None
+        assert cf.senses is not None
+        assert cf.lhs is not None
+        assert cf.rhs is not None
+        assert self.model is not None
+        for (i, name) in enumerate(cf.names):
+            lhs = 0.0
+            for (varname, coeff) in cf.lhs[i]:
+                var = self._varname_to_var[varname]
+                lhs += var * coeff
+            if cf.senses[i] == "=":
+                expr = lhs == cf.rhs[i]
+            elif cf.senses[i] == "<":
+                expr = lhs <= cf.rhs[i]
+            else:
+                expr = lhs >= cf.rhs[i]
+            cl = pe.Constraint(expr=expr, name=name)
+            self.model.add_component(name, cl)
+            self._pyomo_solver.add_constraint(cl)
+            self._cname_to_constr[name] = cl
+        self._termination_condition = ""
+        self._has_lp_solution = False
+        self._has_mip_solution = False
+
     @overrides
     def are_callbacks_supported(self) -> bool:
         return False
 
+    @overrides
+    def are_constraints_satisfied(
+        self,
+        cf: ConstraintFeatures,
+        tol: float = 1e-5,
+    ) -> List[bool]:
+        assert cf.names is not None
+        assert cf.lhs is not None
+        assert cf.rhs is not None
+        assert cf.senses is not None
+        result = []
+        for (i, name) in enumerate(cf.names):
+            lhs = 0.0
+            for (varname, coeff) in cf.lhs[i]:
+                var = self._varname_to_var[varname]
+                lhs += var.value * coeff
+            if cf.senses[i] == "<":
+                result.append(lhs <= cf.rhs[i] + tol)
+            elif cf.senses[i] == ">":
+                result.append(lhs >= cf.rhs[i] - tol)
+            else:
+                result.append(abs(cf.rhs[i] - lhs) < tol)
+        return result
+
     @overrides
     def build_test_instance_infeasible(self) -> Instance:
         return PyomoTestInstanceInfeasible()
@@ -413,6 +463,15 @@ class BasePyomoSolver(InternalSolver):
         self.model.del_component(constr)
         self._pyomo_solver.remove_constraint(constr)
 
+    @overrides
+    def remove_constraints(self, names: List[str]) -> None:
+        assert self.model is not None
+        for name in names:
+            constr = self._cname_to_constr[name]
+            del self._cname_to_constr[name]
+            self.model.del_component(constr)
+            self._pyomo_solver.remove_constraint(constr)
+
     @overrides
     def set_instance(
         self,

miplearn/solvers/tests/__init__.py

@@ -183,42 +183,54 @@ def run_basic_usage_tests(solver: InternalSolver) -> None:
 
     # Fetch constraints (after-mip)
     assert_equals(
-        _round_constraints(solver.get_constraints_old(with_static=False)),
-        {"eq_capacity": Constraint(slack=0.0)},
+        _round(solver.get_constraints(with_static=False)),
+        _filter_attrs(
+            solver.get_constraint_attrs(),
+            ConstraintFeatures(
+                names=("eq_capacity",),
+                slacks=(0.0,),
+            ),
+        ),
     )
 
-    # Build a new constraint
-    cut = Constraint(lhs={"x[0]": 1.0}, sense="<", rhs=0.0)
-    assert not solver.is_constraint_satisfied_old(cut)
+    # Build new constraint and verify that it is violated
+    cf = ConstraintFeatures(
+        names=("cut",),
+        lhs=((("x[0]", 1.0),),),
+        rhs=(0.0,),
+        senses=("<",),
+    )
+    assert_equals(solver.are_constraints_satisfied(cf), [False])
 
-    # Add new constraint and verify that it is listed. Modifying the model should
-    # also clear the current solution.
-    solver.add_constraint(cut, "cut")
+    # Add constraint and verify it affects solution
+    solver.add_constraints(cf)
     assert_equals(
-        _round_constraints(solver.get_constraints_old()),
-        {
-            "eq_capacity": Constraint(
-                lazy=False,
-                lhs={"x[0]": 23.0, "x[1]": 26.0, "x[2]": 20.0, "x[3]": 18.0, "z": -1.0},
-                rhs=0.0,
-                sense="=",
-            ),
-            "cut": Constraint(
-                lazy=False,
-                lhs={"x[0]": 1.0},
-                rhs=0.0,
-                sense="<",
+        _round(solver.get_constraints(with_static=True)),
+        _filter_attrs(
+            solver.get_constraint_attrs(),
+            ConstraintFeatures(
+                names=("eq_capacity", "cut"),
+                rhs=(0.0, 0.0),
+                lhs=(
+                    (
+                        ("x[0]", 23.0),
+                        ("x[1]", 26.0),
+                        ("x[2]", 20.0),
+                        ("x[3]", 18.0),
+                        ("z", -1.0),
+                    ),
+                    (("x[0]", 1.0),),
+                ),
+                senses=("=", "<"),
             ),
-        },
+        ),
     )
-
-    # Re-solve MIP and verify that constraint affects the solution
     stats = solver.solve()
     assert_equals(stats.mip_lower_bound, 1030.0)
-    assert solver.is_constraint_satisfied_old(cut)
+    assert_equals(solver.are_constraints_satisfied(cf), [True])
 
     # Remove the new constraint
-    solver.remove_constraint("cut")
+    solver.remove_constraints(["cut"])
 
     # New constraint should no longer affect solution
     stats = solver.solve()