TST: optimize.milp: remove problematic timeout/iteration test

scipy/optimize/tests/test_milp.py

@@ -272,48 +272,6 @@ def test_infeasible_prob_16609():
     np.testing.assert_equal(res.status, 2)
 
 
-_msg_time = "Time limit reached. (HiGHS Status 13:"
-_msg_iter = "Iteration limit reached. (HiGHS Status 14:"
-
-
-@pytest.mark.skipif(np.intp(0).itemsize < 8,
-                    reason="Unhandled 32-bit GCC FP bug")
-@pytest.mark.slow
-@pytest.mark.timeout(360)
-@pytest.mark.parametrize(["options", "msg"], [({"time_limit": 10}, _msg_time),
-                                              ({"node_limit": 1}, _msg_iter)])
-def test_milp_timeout_16545(options, msg):
-    # Ensure solution is not thrown away if MILP solver times out
-    # -- see gh-16545
-    rng = np.random.default_rng(5123833489170494244)
-    A = rng.integers(0, 5, size=(100, 100))
-    b_lb = np.full(100, fill_value=-np.inf)
-    b_ub = np.full(100, fill_value=25)
-    constraints = LinearConstraint(A, b_lb, b_ub)
-    variable_lb = np.zeros(100)
-    variable_ub = np.ones(100)
-    variable_bounds = Bounds(variable_lb, variable_ub)
-    integrality = np.ones(100)
-    c_vector = -np.ones(100)
-    res = milp(
-        c_vector,
-        integrality=integrality,
-        bounds=variable_bounds,
-        constraints=constraints,
-        options=options,
-    )
-
-    assert res.message.startswith(msg)
-    assert res["x"] is not None
-
-    # ensure solution is feasible
-    x = res["x"]
-    tol = 1e-8  # sometimes needed due to finite numerical precision
-    assert np.all(b_lb - tol <= A @ x) and np.all(A @ x <= b_ub + tol)
-    assert np.all(variable_lb - tol <= x) and np.all(x <= variable_ub + tol)
-    assert np.allclose(x, np.round(x))
-
-
 def test_three_constraints_16878():
     # `milp` failed when exactly three constraints were passed
     # Ensure that this is no longer the case.