### 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)

is_dag_run_conf_overrides_params=is_dag_run_conf_overrides_params,
                    recent_confs=recent_confs,
                )
        if dag.get_is_paused():
            if unpause or not ui_fields_defined:
                flash(f"Unpaused DAG {dag_id}.")
                dag_model = models.DagModel.get_dagmodel(dag_id)
                if dag_model is not None:
                    dag_model.set_is_paused(is_paused=False)
            else:
                flash(
                    f"DAG {dag_id} is paused, unpause if you want to have the triggered run being executed.",
                    "warning",
                )
        try:
            dag.create_dagrun(
                run_type=DagRunType.MANUAL,
                execution_date=execution_date,
                data_interval=dag.timetable.infer_manual_data_interval(run_after=execution_date),
                state=DagRunState.QUEUED,
                conf=run_conf,
                external_trigger=True,
                dag_hash=get_airflow_app().dag_bag.dags_hash.get(dag_id),
                run_id=run_id,
            )
        except (ValueError, ParamValidationError) as ve:
            flash(f"{ve}", "error")
            form = DateTimeForm(data={"execution_date": execution_date})
            
            for k, v in form_fields.items():