Function test_restart

tests/test_IteratedLocalSearch.py:186–228

Tests that restarting clears the history of recent solutions and starts over from scratch.

(ok_small)

def test_restart(ok_small):
    """
    Tests that restarting clears the history of recent solutions and starts
    over from scratch.
    """
    Params = IteratedLocalSearchParams

    sols = [
        Solution(ok_small, [[1, 3], [2, 4]]),  # 22065 (infeas)
        Solution(ok_small, [[1, 2], [3, 4]]),  # 9725
        Solution(ok_small, [[1, 2], [3, 4]]),  # 9725
        Solution(ok_small, [[1, 2], [4, 3]]),  # 9868
    ]

    def run(params: IteratedLocalSearchParams):  # run with given params
        idx = iter(range(len(sols)))
        ils = IteratedLocalSearch(
            ok_small,
            PenaltyManager(initial_penalties=([20], 6, 6)),
            RandomNumberGenerator(42),
            lambda *_, **kw: sols[next(idx)],  # returns sols one at a time
            sols[0],
            params,
        )

        res = ils.run(MaxIterations(len(sols)))
        return res.stats.data

    # First run without a restart. We look back to the current solution from
    # last iteration, which means that we only accept improving solutions.
    curr_costs = [22065, 9725, 9725, 9725]
    params = Params(history_length=1, exhaustive_on_best=False)
    assert_equal([datum.current_cost for datum in run(params)], curr_costs)

    # But here a restart occurs in the third iteration, and that should clear
    # the history. We now accept the worsening solution in the last iteration.
    params = Params(
        num_iters_no_improvement=1,
        history_length=1,
        exhaustive_on_best=False,
    )
    curr_costs = [22065, 9725, 9725, 9868]
    assert_equal([datum.current_cost for datum in run(params)], curr_costs)


def test_exhaustive_search_on_new_best_solution(ok_small):