### 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)

return redirect(url_for("Airflow.index"))
        wwwutils.check_import_errors(dag.fileloc, session)
        wwwutils.check_dag_warnings(dag.dag_id, session)
        root = request.args.get("root")
        if root:
            dag = dag.partial_subset(task_ids_or_regex=root, include_downstream=False, include_upstream=True)
        dag_states = session.execute(
            select(
                _convert_to_date(session, DagRun.execution_date).label("date"),
                DagRun.state,
                func.max(DagRun.data_interval_start).label("data_interval_start"),
                func.max(DagRun.data_interval_end).label("data_interval_end"),
                func.count("*").label("count"),
            )
            .where(DagRun.dag_id == dag.dag_id)
            .group_by(_convert_to_date(session, DagRun.execution_date), DagRun.state)
            .order_by(_convert_to_date(session, DagRun.execution_date).asc())
        ).all()
        data_dag_states = [
            {
                
                
                "date": dr.date if isinstance(dr.date, str) else dr.date.isoformat(),
                "state": dr.state,
                "count": dr.count,
            }
            for dr in dag_states
        ]
        if dag_states and dag_states[-1].data_interval_start and dag_states[-1].data_interval_end:
            last_automated_data_interval = DataInterval(