Implement lazy callbacks & two-phase gap

miplearn/solvers/tests/__init__.py

@@ -7,13 +7,13 @@ from miplearn.problems.knapsack import KnapsackInstance, GurobiKnapsackInstance
 
 
 def _get_instance(solver):
-    if issubclass(solver, BasePyomoSolver):
+    if issubclass(solver, BasePyomoSolver) or isinstance(solver, BasePyomoSolver):
         return KnapsackInstance(
             weights=[23., 26., 20., 18.],
             prices=[505., 352., 458., 220.],
             capacity=67.,
         )
-    if issubclass(solver, GurobiSolver):
+    if issubclass(solver, GurobiSolver) or isinstance(solver, GurobiSolver):
         return GurobiKnapsackInstance(
             weights=[23., 26., 20., 18.],
             prices=[505., 352., 458., 220.],

miplearn/solvers/tests/test_lazy_cb.py

@@ -0,0 +1,27 @@
+#  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 . import _get_instance
+from ... import GurobiSolver
+
+logger = logging.getLogger(__name__)
+
+
+def test_lazy_cb():
+    solver = GurobiSolver()
+    instance = _get_instance(solver)
+    model = instance.to_model()
+
+    def lazy_cb(cb_solver, cb_model):
+        logger.info("x[0] = %.f" % cb_solver.get_value("x", 0))
+        cobj = (cb_model.getVarByName("x[0]") * 1.0, "<", 0.0, "cut")
+        if not cb_solver.is_constraint_satisfied(cobj):
+            cb_solver.add_constraint(cobj)
+
+    solver.set_instance(instance, model)
+    solver.solve(lazy_cb=lazy_cb)
+    solution = solver.get_solution()
+    assert solution["x"][0] == 0.0