### Body

Currently `start_date` is mandatory parameter.
For DAGs with `schedule=None` we can relax this requirement as no scheduling calculation needed so the `start_date` parameter isn't used.

### Committer

- [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.
start_dates = [t.start_date for t in self.tasks if t.start_date]
        if self.start_date is not None:
            start_dates.append(self.start_date)
        earliest = None
        if start_dates:
            earliest = timezone.coerce_datetime(min(start_dates))
        latest = self.end_date
        end_dates = [t.end_date for t in self.tasks if t.end_date]
        if len(end_dates) == len(self.tasks):  
            if self.end_date is not None:
                end_dates.append(self.end_date)
            if end_dates:
                latest = timezone.coerce_datetime(max(end_dates))
        return TimeRestriction(earliest, latest, self.catchup)
    def iter_dagrun_infos_between(
        self,
        earliest: pendulum.DateTime | None,
        latest: pendulum.DateTime,
        *,
        align: bool = True,
    ) -> Iterable[DagRunInfo]:
        """Yield DagRunInfo using this DAG's timetable between given interval.
        DagRunInfo instances yielded if their ``logical_date`` is not earlier
        than ``earliest``, nor later than ``latest``. The instances are ordered
        by their ``logical_date`` from earliest to latest.
        If ``align`` is ``False``, the first run will happen immediately on
        ``earliest``, even if it does not fall on the logical timetable schedule.