### Description

Replace the existing selects with multi-selects that allow you to filter multiple DAG run states and types at the same time, somewhat similar to my prototype:

![image](https://github.com/apache/airflow/assets/1842905/c4ec0793-1ccb-417d-989c-781997416f97)


### Use case/motivation

I'm not sure if it is just me, but sometimes I wish I was able to show multiple DAG run states, especially `running` and `failed`, at the same time. 
This would be especially helpful for busy DAGs on which I want to clear a few failed runs. Without the multi-select, if I switch from `failed` to `running` DAG runs, I need to orient myself again to find the run I just cleared (assuming there are lots of other running DAG runs). _With_ the multi-select, the DAG run I just cleared stays in the same spot and I can check the logs, while clearing some other failed runs.

I'm not sure we need a multi-select for DAG run types as well. I'd tend to say no, but maybe someone else has a use-case for that.

### Related issues

_No response_

### Are you willing to submit a PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"instances": [],
            "label": None,
        },
        "ordering": ["data_interval_end", "execution_date"],
    }
@pytest.fixture
def freeze_time_for_dagruns(time_machine):
    time_machine.move_to("2022-01-02T00:00:00+00:00", tick=False)
    yield
@pytest.mark.usefixtures("freeze_time_for_dagruns")
def test_one_run(admin_client, dag_with_runs: list[DagRun], session):
    """
    Test a DAG with complex interaction of states:
    - One run successful
    - One run partly success, partly running
    - One TI not yet finished
    """
    run1, run2 = dag_with_runs
    for ti in run1.task_instances:
        ti.state = TaskInstanceState.SUCCESS
    for ti in sorted(run2.task_instances, key=lambda ti: (ti.task_id, ti.map_index)):
        if ti.task_id == "task1":
            ti.state = TaskInstanceState.SUCCESS
        elif ti.task_id == "group.mapped":
            if ti.map_index == 0:
                ti.state = TaskInstanceState.SUCCESS
                ti.start_date = pendulum.DateTime(2021, 7, 1, 1, 0, 0, tzinfo=pendulum.UTC)
                ti.end_date = pendulum.DateTime(2021, 7, 1, 1, 2, 3, tzinfo=pendulum.UTC)
            elif ti.map_index == 1:
                ti.state = TaskInstanceState.RUNNING