Fix Gurobi objective

mip/gurobi.py

@@ -535,13 +535,10 @@ def get_objective(self) -> LinExpr:
         st = GRBgetdblattrarray(self._model, attr, 0, self.num_cols(), obj)
         if st != 0:
             raise ParameterNotAvailable("Error getting objective function")
-        obj_expr = xsum(
-            obj[i] * self.model.vars[i]
-            for i in range(self.num_cols())
-            if abs(obj[i]) > 1e-20
-        )
-        obj_expr.const = self.get_objective_const()
-        obj_expr.sense = self.get_objective_sense
+        obj_expr = LinExpr(variables=[self.model.vars[i] for i in range(self.num_cols()) if abs(obj[i]) > 1e-20],
+                           coeffs=[obj[i] for i in range(self.num_cols()) if abs(obj[i]) > 1e-20],
+                           const=self.get_objective_const(),
+                           sense=self.get_objective_sense())
         return obj_expr
 
     def get_objective_const(self) -> float:

test/dbft_test.py

@@ -495,3 +495,4 @@ def test_dbft_mip(solver, pdata):
         m.check_optimization_results()
         if m.status == OptimizationStatus.OPTIMAL:
             assert abs(m.objective_value - opt) <= TOL
+        assert abs(m.objective.x - m.objective_value) <= TOL

test/test_model.py

@@ -1260,3 +1260,38 @@ def test_query_attributes_of_lin_expr(solver):
     assert constr_expr.violation is None
 
     m.optimize()
+
+@pytest.mark.parametrize("solver", SOLVERS)
+def test_objective(solver):
+    m = Model(solver_name=solver, sense=MAXIMIZE)
+    x = m.add_var(name="x", lb=0, ub=1)
+    y = m.add_var(name="y", lb=0, ub=1)
+
+    m.objective = x - y + 0.5
+    assert m.objective.x is None
+
+    # Make sure that we can access the objective and it's correct
+    assert len(m.objective.expr) == 2
+    assert m.objective.expr[x] == 1
+    assert m.objective.expr[y] == -1
+    assert m.objective.const == 0.5
+
+    status = m.optimize()
+    assert status == OptimizationStatus.OPTIMAL
+    assert m.objective_value == 1.5
+    assert m.objective_value == m.objective.x
+
+
+    # Test changing the objective
+    m.objective = x + y + 1.5
+    m.sense = MINIMIZE
+
+    assert len(m.objective.expr) == 2
+    assert m.objective.expr[x] == 1
+    assert m.objective.expr[y] == 1
+    assert m.objective.const == 1.5
+
+    status = m.optimize()
+    assert status == OptimizationStatus.OPTIMAL
+    assert m.objective_value == 1.5
+    assert m.objective_value == m.objective.x